Transposition of native chromatin for personal epigenomics

ABSTRACT

Provided herein is a method for analyzing polynucleotides such as genomic DNA. In certain embodiments, the method comprises: (a) treating chromatin isolated from a population of cells with an insertional enzyme complex to produce tagged fragments of genomic DNA; (b) sequencing a portion of the tagged fragments to produce a plurality of sequence reads; and (c) making an epigenetic map of a region of the genome of the cells by mapping information obtained from the sequence reads to the region. A kit for performing the method is also provided.

CROSS-REFERENCING

This application claims the benefit of U.S. Provisional application Ser.No. 61/826,728, filed on May 23, 2013, which application is incorporatedby reference herein in its entirety.

GOVERNMENT SUPPORT

This invention was made with Government support under contractsAI057229, HG000044, and NS073015 awarded by the National Institutes ofHealth. The Government has certain rights in the invention.

BACKGROUND

Eukaryotic genomes are hierarchically packaged into chromatin, and thenature of this packaging plays a central role in gene regulation. Majorinsights into the epigenetic information encoded within thenucleoprotein structure of chromatin have come from high-throughput,genome-wide methods for separately assaying the chromatin accessibility(“open chromatin”), nucleosome positioning, and transcription factor(TF) occupancy. While published protocols exist, those methods requiremillions of cells as starting material, complex and time-consumingsample preparations, and cannot simultaneously probe the interplay ofnucleosome positioning, chromatin accessibility, and TF binding. Theselimitations are problematic in three major ways: First, current methodscan average over and “drown out” heterogeneity in cellular populations.Second, cells must often be grown ex vivo to obtain sufficientbiomaterials, perturbing the in vivo context and modulating theepigenetic state in unknown ways. Third, input requirements oftenprevent application of these assays to well-defined clinical samples,precluding generation of “personal epigenomes” in diagnostic timescales.Provided herein are methods for analyzing polynucleotides, includingtheir accessibility and their structure, that can overcome theselimitation(s). Also provided are single-cell methods that can providehigher sensitivity and further information on chromatin accessibility,including cell-to-cell variability, to potentially enable its use as abiomarker.

SUMMARY

Provided herein is a method for analyzing polynucleotides such asgenomic DNA. In certain embodiments, the method comprises: (a) treatingchromatin isolated from a population of cells with a transposase andmolecular tags to produce tagged fragments of polynucleotides; (b)sequencing a portion of the tagged fragments to produce a plurality ofsequence reads; and (c) making an epigenetic map of a region of thegenome of the cells by mapping information obtained from the sequencereads to the region.

In some cases, the information is obtained using the nucleotidesequences at the beginning and, optionally, the end of a sequence read.In some cases, the information mapped in (c) is selected from one ormore of: (i) cleavage sites for the transposase; (ii) the sizes of thefragments produced in step (a); (iii) sequence read length; (iii) thepositions of sequence reads of a defined range in length; and (iv)sequence read abundance. In some instances, the fragments of a definedsize range are nucleosome-free fragments.

In some instances, the epigenetic map shows one or more of: (i) aprofile of chromatin accessibility along the region; (ii) DNA bindingprotein occupancy for a binding site in the region; (iii)nucleosome-free DNA in the region; (iv) positioning of nucleosomes alongthe region; and/or (v) chromatin states. In some cases, the method canfurther comprise measuring global occupancy of a binding site for theDNA binding protein. The DNA binding protein can, for example, be atranscription factor.

In some cases, the population of cells can be composed of about 500 to100,000 cells. The cells can be isolated from an individual, such asfrom the blood of the individual. In some examples, the cells can be ofthe same cell type. In some examples, the cells can be FACS—selectedcells.

In some instances, the treating step (a) can comprise: isolating nucleifrom the population of cells; and combining the isolated nuclei with theinsertional enzyme complex, wherein the combining results in both lysisof the nuclei to release the chromatin and production of the taggedfragments of genomic DNA. In some examples, the transposase can bederived from Tn5 transposase. In other examples, the transposase can bederived from MuA transposase. In further examples, the transposase canbe derived from Vibhar transposase (e.g. from Vibrio harveyi).

The present disclosure also provides a method for comparing two samplescomprising: (a) analyzing a first population of cells to produce a firstepigenetic map; and (b) analyzing a second population of cells toproduce a second epigenetic map; and (c) comparing the first epigeneticmap to the second epigenetic map. For example, the first population ofcells and the second population of cells can be collected from the sameindividual at different times. Alternatively, the first population ofcells and the second population of cells can be different populations ofcells collected from different individuals.

The present disclosure further provides a diagnostic method, comprising:analyzing chromatin from a patient to produce an epigenetic map; andproviding a diagnosis or prognosis based on the epigenetic map.

The present disclosure provides a method for determining accessibilityof a polynucleotide at a site, wherein the polynucleotide is from a cellsample, comprising: (a) inserting a plurality of molecular tags with aninsertional enzyme into the polynucleotide; and (b) using the moleculartags to determine accessibility at the site. The method can furthercomprise using the determined accessibility to identify one or moreproteins that are bound to the polynucleotide at the site. In somecases, at least one of the proteins is a transcription factor. Themethod can also comprise using the molecular tags to generate anaccessibility map of the polynucleotide.

The present disclosure also provides a method for analyzing thethree-dimensional structure of a polynucleotide from a cell sample,comprising: (a) inserting a plurality of molecular tags with aninsertional enzyme into the polynucleotide; and (b) using the moleculartags to analyze the three-dimensional structure of the polynucleotide.In some cases, the insertional enzyme can comprise two or more enzymaticmoieties wherein each of the enzymatic moieties inserts a commonsequence into the polynucleotide. The enzymatic moieties can be linkedtogether. The common sequence can comprise a common barcode. Theenzymatic moieties can comprise transposases. The polynucleotide canfragmented into a plurality of fragments during step (a), wherein thefragments comprising the common barcode are determined to be inproximity in the three-dimensional structure of the polynucleotide.

The polynucleotide can be fragmented into a plurality of fragmentsduring the insertion. The method can further comprise amplifying thefragments. The accessibility can be determined by sequencing thefragments and thereby generating a plurality of sequencing reads. Thefragments can, for example, be sequenced by a high-throughput sequencingtechnique. The method can further comprise normalizing the sequencingreads based on the sequence insertion preference of the insertionalenzyme. The length of the sequenced reads can also be used to determinea chromatin state annotation.

The cell sample can be permeabilized to allow access for the insertionalenzyme. In some cases, the nuclei in the cell sample can be minimallyperturbed during the permeabilization. The cell sample can bepermeabilized using a permeabilization agent including, but not limitedto, NP40, digitonin, tween, streptolysin, and/or cationic lipids. Thecell sample can also be permeabilized using hypotonic shock and/orultrasonication.

The method can further comprise analyzing a disease state in a subjectbased on the accessibility of the specific site, wherein the cell sampleis obtained from the subject. The cell sample and/or the polynucleotidescan also be divided into a plurality of portions, which may beoptionally divided based on the molecular tags. The method can furthercomprise analyzing a phenotype of the cell sample. In some cases, thephenotype can be correlated to the accessibility of the site.

The insertion can be facilitated by addition of one or more divalentcations. In some cases, the one or more divalent cations can comprisemagnesium. In some cases, the one or more divalent cations can comprisemanganese.

The cell sample can be obtained from a primary source. The cell samplecan consist of less than about 500,000 cells, or even a single cell. Thepolynucleotide can be bound to a plurality of association molecules. Theassociation molecules can comprise proteins, such as histones. Theinsertional enzyme can be a transposase. In some cases, the transposasecan be derived from a Tn5 transposase. In other cases, the transposasecan be derived from a MuA transposase. In further cases, the transposasecan be derived from a Vibhar transposase (e.g. from Vibrio harveyi). Insome cases, the molecular tags can comprise sequencing adaptors, whichmay further comprise a barcode label. The barcode label can comprise aunique sequence. In other cases, the molecular tags can comprisefluorescence tags. The insertional enzyme can further comprise anaffinity tag, which may optionally be an antibody that binds to atranscription factor, a modified nucleosome, and/or a modified nucleicacid. The modified nucleic acid can, for example be a methylated orhydroxymethylated DNA. The affinity tag can also be a single-strandednucleic acid, which may optionally bind to a target nucleic acid. Theinsertional enzyme can further comprise a nuclear localization signal.

The present disclosure also provides compositions. The composition cancomprise a polynucleotide, an insertional enzyme and an insert element,wherein: the insert element comprises a nucleic acid comprising apredetermined sequence; and the insertional enzyme further comprises anaffinity tag. The composition can also comprise a polynucleotide, aninsertional enzyme and an insert element, wherein: the insertionalenzyme comprises two or more enzymatic moieties; and the enzymaticmoieties are linked together. The affinity tag can be an antibody, whichmay optionally be bound to a transcription factor, a modifiednucleosome, and/or a modified nucleic acid. The modified nucleic acidcan be, for example, a methylated or hydroxymethylated DNA. The affinitytag can also be a single-stranded nucleic acid, which may be optionallybound to a target nucleic acid. The insert element can be bound to theinsertional enzyme and the insertional enzyme is bound to thepolynucleotide. The polynucleotide can be further bound to a pluralityof association molecules. The association molecules can compriseproteins such as, for example, histones.

The present disclosure further provides kits. The kit can comprise: (a)reagents for isolating nuclei from a population of cells; (b) aninsertional enzyme complex, and (c) transposase reaction buffer. In somecases, the components of the kit can be configured such that, combiningthe reaction buffer, transposon tags and adaptors with nuclei in vitroresults in both lysis of the nuclei to release chromatin and productionof tagged fragments of genomic DNA. The kit can also comprise: a celllysis buffer; an insertional enzyme comprising an affinity tag; and aninsert element comprising a nucleic acid, wherein the nucleic acidcomprises a predetermined sequence. The kit can further comprise: a celllysis buffer; an insertional enzyme comprising two or more enzymaticmoieties, wherein the enzymatic moieties are linked together; and (c) aninsert element. The affinity tag can be an antibody, which canoptionally bind to a transcription factor, a modified nucleosome, and/ora modified nucleic acid. The modified nucleic acid can be, for example,a methylated or hydroxymethylated DNA. The affinity can also be asingle-stranded nucleic acid, which may be optionally bound to a targetnucleic acid.

These and other features of the present teachings are set forth herein.

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, or patent application wasspecifically and individually indicated to be incorporated by reference.

BRIEF DESCRIPTION OF THE FIGURES

The skilled artisan will understand that the drawings, described below,are for illustration purposes only. The drawings are not intended tolimit the scope of the present teachings in any way.

FIGS. 1A-1C: ATAC-seq is a sensitive, accurate probe of open chromatinstate. (a) ATAC-seq reaction schematic. Transposase (green), loaded withsequencing adapters (red and blue), inserts only in regions of openchromatin (nucleosomes in grey) and generates sequencing libraryfragments that can be PCR amplified. (b) Approximate reported inputmaterial and sample preparation time requirements for genome-widemethods of open chromatin analysis. (c) A comparison of ATAC-seq toother open chromatin assays at a locus in GM12878 lymphoblastoid cellsdisplaying high concordance. Lower ATAC-seq track was generated from 500FACS-sorted cells.

FIGS. 2A-2B: ATAC-seq provides genome-wide information on chromatincompaction. (a) ATAC-seq fragment sizes generated from GM12878 nuclei(red) indicate chromatin-dependent periodicity with a spatial frequencyconsistent with nucleosomes, as well as a high frequency periodicityconsistent with the pitch of the DNA helix for fragments less than 200bp. (Inset) log-transformed histogram shows clear periodicity persiststo 6 nucleosomes. (b) Normalized read enrichments for 7 classes ofchromatin state previously defined.

FIGS. 3A-3E: ATAC-seq provides genome-wide information on nucleosomepositioning in regulatory regions. (a) An example locus containing twotranscription start sites (TSSs) showing nucleosome free read track,calculated nucleosome track (Methods), as well as DNase, MNase, andH3K27ac, H3K4me3, and H2A.Z tracks for comparison. (b) ATAC-seq (198million paired reads) and MNase-seq (4 billion single-end reads from ref23) nucleosome signal shown for all active TSSs (n=64,836), TSSs aresorted by CAGE expression. (c) TSSs are enriched for nucleosome freefragments, and show phased nucleosomes similar to those seen byMNase-seq at the −2, −1, +1, +2, +3 and +4 positions. (d) Relativefraction of nucleosome associated vs. nucleosome free (NFR) bases in TSSand distal sites (see Methods). (e) Hierarchical clustering of DNAbinding factor position with respect to the nearest nucleosome dyadwithin accessible chromatin reveals distinct classes of DNA bindingfactors. Factors strongly associated with nucleosomes are enriched forchromatin remodelers.

FIGS. 4A-4C: ATAC-seq assays genome-wide factor occupancy. (a) CTCFfootprints observed in ATAC-seq and DNase-seq data, at a specific locuson chr1. (b) Aggregate ATAC-seq footprint for CTCF (motif shown)generated over binding sites within the genome (c) CTCF predictedbinding probability inferred from ATAC-seq data, position weight matrix(PWM) scores for the CTCF motif, and evolutionary conservation (PhyloP).Right-most column is the CTCF ChIP-seq data (ENCODE) for this GM12878cell line, demonstrating high concordance with predicted bindingprobability.

FIGS. 5A-5D: ATAC-seq enables real-time personal epigenomics. (a) Workflow from standard blood draws. (b) Serial ATAC-seq data from probandT-cells over three days. (c) Example of application of ATAC-seq data(green track) to prioritize candidate TF drug targets. Among identifiedTF binding sites proximal to cytokine gene IL2 that can be targeted byFDA-approved drugs, only NFAT is engaged in proband T-cells. ATAC-seqfootprint prediction is confirmed by alignment with published NFATChIP-seq data (blue track, data from ref³⁵). (d) Cell type-specificregulatory network from proband T cells compared with GM12878 B-cellline. Each row or column is the footprint profile of a TF versus that ofall other TFs in the same cell type. Color indicates relative similarity(yellow) or distinctiveness (blue) in T versus B cells. NFAT is one ofthe most highly differentially regulated TFs (red box) whereas canonicalCTCF binding is essentially similar in T and B cells.

FIG. 6: ATAC-seq peak intensity correlates well with DNase-seq peakintensity. Peaks in Duke DNase-seq (down sampled to 60×10⁶ reads), UWDNase-seq (40×10⁶ reads), and ATAC-seq data (60×10⁶ paired-end reads)were called using ZINBA (Rashid et al Genome Biol. 2011 12: R67).Because each data set has different read lengths we chose to filter forpeaks within mappable regions (Duke DNase-seq=20 bp reads, UWDNase-Seq=36 bp reads and ATAC-Seq=paired-end 50 bp reads). Thelog10(read intensity) was compared for (A) Duke DNase-seq and ATAC-seq,(B) UW DNase-seq and ATAC-seq, and (C) UW DNAse-seq and Duke DNase-seq.Technical reproducibility of ATAC-seq data is shown in D.

FIG. 7: ATAC-seq captures a large fraction of DNase identified peaks.Peaks were called for all data sets using ZINBA. The venn-diagram showsoverlap of the peak calls between each method. Below: The majority ofATAC-seq reads are in intense peaks that intersect with Duke and UWDNase-seq peaks. The total fraction of reads within peaks called fromATAC-seq, UW DNase-seq, and Duke DNase-seq, as well as the intersectionsof these data are shown. More than 65% of reads from all three methodsare found in the intersection of the three methods' peaks, suggestingthat strong well-stereotyped peaks are detected by all methods. Tablecell color is proportional to fraction of reads.

FIG. 8: Graphs of the number of reads overlapping the set of openchromatin regions identified by Duke DNase, UW DNase and FAIRE inGM12878 cells compared to a set of background regions, wherein todetermine the read depth required for detecting open chromatin sitessensitivity and specificity was assessed at varying read depths,including 50 k, 100 k, 500 k, 10 million and 50 million reads. Thebottom graph shows the performance of ATAC-seq in GM12878 cells wasassessed using 500, 5,000 or 50,000 cells as starting material.

FIG. 9: Tn5 insertion preferences in genomic DNA and chromatin.Nucleotide frequency scores represent the observed nucleotide frequencyof each base, nucleotide frequencies are normalized to 1. The x=0position represents the read start, and the dotted line represents thesymmetry axis of the Tn5 dimer. We see no substantial differencesbetween Tn5 insertion preferences between purified genomic DNA and humanchromatin, suggesting that the local insertion preference into chromatinis identical to that found in naked genomic DNA. These reported sequencepreferences are similar to those previously reported (main text ref 11).

FIG. 10: Graph of the average intensity per base of each feature atevery ATAC-seq peak; all ENCODE ChIP data was normalized to input; datahas been processed using a sliding window of 200 peaks.

FIG. 11: ATAC-seq of various cell numbers. A representative UCSC genomebrowser track of data from different starting numbers of cells forATAC-seq. This same locus is also shown in FIG. 1b of the main text. Inorder: 500 cells were isolated using FACS and two replicates of 500cells and 5,000 cells were done by a simple dilution from cell culture.For comparison, the bottom track represents 50,000 cells, also show inFIG. 1 b. This figure demonstrates that we are able to capture openchromatin sites from as few as 500 cells.

FIG. 12: Fitting nucleosome peaks in ATAC-seq fragment size distributionto enable nucleosome occupancy measurements. The observed fragmentdistribution was partitioned into four populations of reads—readsexpected to originate from open DNA, and reads that span 1, 2 or 3putative nucleosomes. To enable this partitioning of the data, theATAC-seq fragment distribution was fit to the sum of 1) an exponentialfunction for fragment distribution pattern at insert sizes below onenucleosome, and 2) 5 Gaussians to the distributions arising fromprotection from one, two, three, four and five nucleosomes. The sum ofthese fits is shown (black dotted line) is similar to the observedfragment distribution (blue line). Vertical dotted lines are boundariesfor identification of fragments as originating from the nucleosome-free(<100 bps), 1-nucleosome, 2-nucleosome and 3-nucleosome regions. Dottedlines were set to ensure that <10% of fragments originate fromneighboring, as defined by our fit.

FIG. 13: Select set of transcription factor footprints detected byATAC-seq in GM12878 cells. For the indicated transcription factors theaggregate signal of ATAC-seq reads were computed using CENTIPEDE on thegenome-wide sets of sites matching the corresponding motif. Reads werecalculated in the region +/−100 bp of the motif boundary. The verticaldashed lines indicate the boundaries of the motifs.

FIG. 14: Prediction of CTCF binding sites using ATAC-seq and DNasefootprinting with CENTIPEDE. Prediction of CTCF binding sites wasassessed using the genome-wide set of CTCF motifs sorted by theposterior probability reported by CENTIPEDE. Those overlapping CTCFChIP-seq peaks were used as the positive set and all others wereconsidered as the negative set. This yielded an area under the curve(AUC) of 0.92, which suggests specific and sensitive binding inferencefor CTCF. Duke DNase and UW DNase data were used with the same settingsof CENTIPEDE, and ROC plots are shown. ATAC-seq data consisted of198×10⁶ paired reads, Duke DNase-comprised 245×10⁶ reads, and UW DNasecomprised 48×10⁶ reads.

FIG. 15: T-cell specific NFAT regulation: Examples of T-cell-specificNFAT target genes predicted by ATAC-seq and confirmed by alignment withNFAT ChIP-seq (data from main text ref 35).

FIG. 16: ATAC-seq of FACS-purified cell populations from human blood.(A) From a standard blood draw, we used Fluorescence-Activated CellSorting (FACS) to purify CD4+ T-cells, CD8+ T-cells, and CD14+monocytes. Each population generated successful ATAC-seq data (B) andrevealed cell-type specific open chromatin sites at knownlineage-specific genes.

FIG. 17: Detection of allele specific open chromatin in GM12878 cellswith ATAC-seq. Using publicly available variant data, we measured theallele frequency in open chromatin regions at putative heterozygousloci. Because of potential for spurious heterozygous sites, we requiredmore than two reads to validate the heterozygosity of the allele. Redpoints (n=167) are candidate allele specific open chromatin sites atp<10⁻⁵, while grey (n=900) represent candidates at p<0.01. P-values werecalculated using a Bayesian model developed by Audic et al (GenomeResearch 1997 7, 986-995).

FIG. 18: Transposases can serve as an open-chromatin stain. By loadingTn5 transposes with fluorescently labeled DNA adapters, transpositionevents, shown in green, are primarily localized to the nucleus, andexhibit a punctate pattern consistent with higher order organization.

FIG. 19: Single-cell ATAC-seq data from a single nucleus (blue) showclear peak at the expected positions of open-chromatin genome widecompared to 50,000 cells.

FIG. 20: Single cell insert length distribution matches that from 50,000cells showing periodicity due to the presence of nucleosomes.

DEFINITIONS

Unless defined otherwise herein, all technical and scientific terms usedherein have the same meaning as commonly understood by one of ordinaryskill in the art to which this invention belongs. Although any methodsand materials similar or equivalent to those described herein can beused in the practice or testing of the present invention, the preferredmethods and materials are described.

All patents and publications, including all sequences disclosed withinsuch patents and publications, referred to herein are expresslyincorporated by reference.

Numeric ranges are inclusive of the numbers defining the range. Unlessotherwise indicated, nucleic acids are written left to right in 5′ to 3′orientation; amino acid sequences are written left to right in amino tocarboxy orientation, respectively.

The headings provided herein are not limitations of the various aspectsor embodiments of the invention. Accordingly, the terms definedimmediately below are more fully defined by reference to thespecification as a whole.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention belongs. Singleton, et al., DICTIONARYOF MICROBIOLOGY AND MOLECULAR BIOLOGY, 2D ED., John Wiley and Sons, NewYork (1994), and Hale & Markham, THE HARPER COLLINS DICTIONARY OFBIOLOGY, Harper Perennial, N.Y. (1991) provide one of skill with thegeneral meaning of many of the terms used herein. Still, certain termsare defined below for the sake of clarity and ease of reference.

The term “sample” as used herein relates to a material or mixture ofmaterials, typically containing one or more analytes of interest. In oneembodiment, the term as used in its broadest sense, refers to any plant,animal or viral material containing DNA or RNA, such as, for example,tissue or fluid isolated from an individual (including withoutlimitation plasma, serum, cerebrospinal fluid, lymph, tears, saliva andtissue sections) or from in vitro cell culture constituents, as well assamples from the environment.

The term “nucleic acid sample,” as used herein, denotes a samplecontaining nucleic acids. Nucleic acid samples used herein may becomplex in that they contain multiple different molecules that containsequences. Genomic DNA samples from a mammal (e.g., mouse or human) aretypes of complex samples. Complex samples may have more than about 10⁴,10⁵, 10⁶ or 10⁷, 10⁸, 10⁹ or 10¹⁰ different nucleic acid molecules. ADNA target may originate from any source such as genomic DNA, or anartificial DNA construct. Any sample containing nucleic acid, e.g.,genomic DNA from tissue culture cells or a sample of tissue, may beemployed herein.

The term “mixture,” as used herein, refers to a combination of elements,that are interspersed and not in any particular order. A mixture isheterogeneous and not spatially separable into its differentconstituents. Examples of mixtures of elements include a number ofdifferent elements that are dissolved in the same aqueous solution and anumber of different elements attached to a solid support at randompositions (i.e., in no particular order). A mixture is not addressable.To illustrate by example, an array of spatially separated surface-boundpolynucleotides, as is commonly known in the art, is not a mixture ofsurface-bound polynucleotides because the species of surface-boundpolynucleotides are spatially distinct and the array is addressable.

The term “nucleotide” is intended to include those moieties that containnot only the known purine and pyrimidine bases, but also otherheterocyclic bases that have been modified. Such modifications includemethylated purines or pyrimidines, acylated purines or pyrimidines,alkylated riboses or other heterocycles. In addition, the term“nucleotide” includes those moieties that contain hapten or fluorescentlabels and may contain not only conventional ribose and deoxyribosesugars, but other sugars as well. Modified nucleosides or nucleotidesalso include modifications on the sugar moiety, e.g., wherein one ormore of the hydroxyl groups are replaced with halogen atoms or aliphaticgroups, or are functionalized as ethers, amines, or the like.

The term “nucleic acid” and “polynucleotide” are used interchangeablyherein to describe a polymer of any length, e.g., greater than about 2bases, greater than about 10 bases, greater than about 100 bases,greater than about 500 bases, greater than 1000 bases, greater than10,000 bases, greater than 100,000 bases, greater than about 1,000,000,up to about 10¹⁰ or more bases composed of nucleotides, e.g.,deoxyribonucleotides or ribonucleotides, and may be producedenzymatically or synthetically (e.g., PNA as described in U.S. Pat. No.5,948,902 and the references cited therein) which can hybridize withnaturally occurring nucleic acids in a sequence specific manneranalogous to that of two naturally occurring nucleic acids, e.g., canparticipate in Watson-Crick base pairing interactions.Naturally-occurring nucleotides include guanine, cytosine, adenine,thymine, uracil (G, C, A, T and U respectively). DNA and RNA have adeoxyribose and ribose sugar backbone, respectively, whereas PNA'sbackbone is composed of repeating N-(2-aminoethyl)-glycine units linkedby peptide bonds. In PNA various purine and pyrimidine bases are linkedto the backbone by methylenecarbonyl bonds. A locked nucleic acid (LNA),often referred to as inaccessible RNA, is a modified RNA nucleotide. Theribose moiety of an LNA nucleotide is modified with an extra bridgeconnecting the 2′ oxygen and 4′ carbon. The bridge “locks” the ribose inthe 3′-endo (North) conformation, which is often found in the A-formduplexes. LNA nucleotides can be mixed with DNA or RNA residues in theoligonucleotide whenever desired. The term “unstructured nucleic acid,”or “UNA,” is a nucleic acid containing non-natural nucleotides that bindto each other with reduced stability. For example, an unstructurednucleic acid may contain a G′ residue and a C′ residue, where theseresidues correspond to non-naturally occurring forms, i.e., analogs, ofG and C that base pair with each other with reduced stability, butretain an ability to base pair with naturally occurring C and Gresidues, respectively. Unstructured nucleic acid is described inUS20050233340, which is incorporated by reference herein for disclosureof UNA.

The term “oligonucleotide” as used herein denotes a single-strandedmultimer of nucleotide of from about 2 to 200 nucleotides, up to 500nucleotides in length. Oligonucleotides may be synthetic or may be madeenzymatically, and, in some embodiments, are 30 to 150 nucleotides inlength. Oligonucleotides may contain ribonucleotide monomers (i.e., maybe oligoribonucleotides) or deoxyribonucleotide monomers, or bothribonucleotide monomers and deoxyribonucleotide monomers. Anoligonucleotide may be 10 to 20, 21 to 30, 31 to 40, 41 to 50, 51 to 60,61 to 70, 71 to 80, 80 to 100, 100 to 150 or 150 to 200 nucleotides inlength, for example.

“Primer” means an oligonucleotide, either natural or synthetic, that iscapable, upon forming a duplex with a polynucleotide template, of actingas a point of initiation of nucleic acid synthesis and being extendedfrom its 3′ end along the template so that an extended duplex is formed.The sequence of nucleotides added during the extension process isdetermined by the sequence of the template polynucleotide. Usuallyprimers are extended by a DNA polymerase. Primers are generally of alength compatible with their use in synthesis of primer extensionproducts, and are usually in the range of between 8 to 100 nucleotidesin length, such as 10 to 75, 15 to 60, 15 to 40, 18 to 30, 20 to 40, 21to 50, 22 to 45, 25 to 40, and so on. Typical primers can be in therange of between 10-50 nucleotides long, such as 15-45, 18-40, 20-30,21-25 and so on, and any length between the stated ranges. In someembodiments, the primers are usually not more than about 10, 12, 15, 20,21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50, 55, 60, 65, or70 nucleotides in length.

Primers are usually single-stranded for maximum efficiency inamplification, but may alternatively be double-stranded. Ifdouble-stranded, the primer is usually first treated to separate itsstrands before being used to prepare extension products. Thisdenaturation step is typically effected by heat, but may alternativelybe carried out using alkali, followed by neutralization. Thus, a“primer” is complementary to a template, and complexes by hydrogenbonding or hybridization with the template to give a primer/templatecomplex for initiation of synthesis by a polymerase, which is extendedby the addition of covalently bonded bases linked at its 3′ endcomplementary to the template in the process of DNA synthesis.

The term “hybridization” or “hybridizes” refers to a process in which aregion of nucleic acid strand anneals to and forms a stable duplex,either a homoduplex or a heteroduplex, under normal hybridizationconditions with a second complementary nucleic acid strand, and does notform a stable duplex with unrelated nucleic acid molecules under thesame normal hybridization conditions. The formation of a duplex isaccomplished by annealing two complementary nucleic acid strand regionin a hybridization reaction. The hybridization reaction can be made tobe highly specific by adjustment of the hybridization conditions (oftenreferred to as hybridization stringency) under which the hybridizationreaction takes place, such that two nucleic acid strands will not form astable duplex, e.g., a duplex that retains a region ofdouble-strandedness under normal stringency conditions, unless the twonucleic acid strands contain a certain number of nucleotides in specificsequences which are substantially or completely complementary. “Normalhybridization or normal stringency conditions” are readily determinedfor any given hybridization reaction. See, for example, Ausubel et al.,Current Protocols in Molecular Biology, John Wiley & Sons, Inc., NewYork, or Sambrook et al., Molecular Cloning: A Laboratory Manual, ColdSpring Harbor Laboratory Press. As used herein, the term “hybridizing”or “hybridization” refers to any process by which a strand of nucleicacid binds with a complementary strand through base pairing.

A nucleic acid is considered to be “selectively hybridizable” to areference nucleic acid sequence if the two sequences specificallyhybridize to one another under moderate to high stringency hybridizationand wash conditions. Moderate and high stringency hybridizationconditions are known (see, e.g., Ausubel, et al., Short Protocols inMolecular Biology, 3rd ed., Wiley & Sons 1995 and Sambrook et al.,Molecular Cloning: A Laboratory Manual, Third Edition, 2001 Cold SpringHarbor, N.Y.). One example of high stringency conditions includehybridization at about 42° C. in 50% formamide, 5×SSC, 5× Denhardt'ssolution, 0.5% SDS and 100 μg/ml denatured carrier DNA followed bywashing two times in 2×SSC and 0.5% SDS at room temperature and twoadditional times in 0.1×SSC and 0.5% SDS at 42° C.

The term “duplex,” or “duplexed,” as used herein, describes twocomplementary polynucleotide region that are base-paired, i.e.,hybridized together.

The term “amplifying” as used herein refers to the process ofsynthesizing nucleic acid molecules that are complementary to one orboth strands of a template nucleic acid. Amplifying a nucleic acidmolecule may include denaturing the template nucleic acid, annealingprimers to the template nucleic acid at a temperature that is below themelting temperatures of the primers, and enzymatically elongating fromthe primers to generate an amplification product. The denaturing,annealing and elongating steps each can be performed one or more times.In certain cases, the denaturing, annealing and elongating steps areperformed multiple times such that the amount of amplification productis increasing, often times exponentially, although exponentialamplification is not required by the present methods. Amplificationtypically requires the presence of deoxyribonucleoside triphosphates, aDNA polymerase enzyme and an appropriate buffer and/or co-factors foroptimal activity of the polymerase enzyme. The term “amplificationproduct” refers to the nucleic acids, which are produced from theamplifying process as defined herein.

The terms “determining,” “measuring,” “evaluating,” “assessing,”“assaying,” and “analyzing” are used interchangeably herein to refer toany form of measurement, and include determining if an element ispresent or not. These terms include both quantitative and/or qualitativedeterminations. Assessing may be relative or absolute. “Assessing thepresence of” includes determining the amount of something present, aswell as determining whether it is present or absent.

The term “using” has its conventional meaning, and, as such, meansemploying, e.g., putting into service, a method or composition to attainan end. For example, if a program is used to create a file, a program isexecuted to make a file, the file usually being the output of theprogram. In another example, if a computer file is used, it is usuallyaccessed, read, and the information stored in the file employed toattain an end. Similarly if a unique identifier, e.g., a barcode isused, the unique identifier is usually read to identify, for example, anobject or file associated with the unique identifier.

The term “ligating,” as used herein, refers to the enzymaticallycatalyzed joining of the terminal nucleotide at the 5′ end of a firstDNA molecule to the terminal nucleotide at the 3′ end of a second DNAmolecule.

A “plurality” contains at least 2 members. In certain cases, a pluralitymay have at least 2, at least 5, at least 10, at least 100, at least100, at least 10,000, at least 100,000, at least 10⁶, at least 10⁷, atleast 10⁸ or at least 10⁹ or more members.

If two nucleic acids are “complementary,” they hybridize with oneanother under high stringency conditions. The term “perfectlycomplementary” is used to describe a duplex in which each base of one ofthe nucleic acids base pairs with a complementary nucleotide in theother nucleic acid. In many cases, two sequences that are complementaryhave at least 10, e.g., at least 12 or 15 nucleotides ofcomplementarity.

An “oligonucleotide binding site” refers to a site to which anoligonucleotide hybridizes in a target polynucleotide. If anoligonucleotide “provides” a binding site for a primer, then the primermay hybridize to that oligonucleotide or its complement.

The term “strand” as used herein refers to a nucleic acid made up ofnucleotides covalently linked together by covalent bonds, e.g.,phosphodiester bonds. In a cell, DNA usually exists in a double-strandedform, and as such, has two complementary strands of nucleic acidreferred to herein as the “top” and “bottom” strands. In certain cases,complementary strands of a chromosomal region may be referred to as“plus” and “minus” strands, the “first” and “second” strands, the“coding” and “noncoding” strands, the “Watson” and “Crick” strands orthe “sense” and “antisense” strands. The assignment of a strand as beinga top or bottom strand is arbitrary and does not imply any particularorientation, function or structure. The nucleotide sequences of thefirst strand of several exemplary mammalian chromosomal regions (e.g.,BACs, assemblies, chromosomes, etc.) is known, and may be found inNCBI's Genbank database, for example.

The term “top strand,” as used herein, refers to either strand of anucleic acid but not both strands of a nucleic acid. When anoligonucleotide or a primer binds or anneals “only to a top strand,” itbinds to only one strand but not the other. The term “bottom strand,” asused herein, refers to the strand that is complementary to the “topstrand.” When an oligonucleotide binds or anneals “only to one strand,”it binds to only one strand, e.g., the first or second strand, but notthe other strand.

The term “sequencing,” as used herein, refers to a method by which theidentity of at least 10 consecutive nucleotides (e.g., the identity ofat least 20, at least 50, at least 100 or at least 200 or moreconsecutive nucleotides) of a polynucleotide is obtained.

The terms “next-generation sequencing” or “high-throughput sequencing”refer to the so-called parallelized sequencing-by-synthesis orsequencing-by-ligation platforms currently employed by Illumina, LifeTechnologies, and Roche, etc. Next-generation sequencing methods mayalso include nanopore sequencing methods or electronic-detection basedmethods such as Ion Torrent technology commercialized by LifeTechnologies or single-molecule fluorescence-based method commercializedby Pacific Biosciences.

The term “barcode sequence” or “molecular barcode,” as used herein,refers to a unique sequence of nucleotides used to a) identify and/ortrack the source of a polynucleotide in a reaction and/or b) count howmany times an initial molecule is sequenced (e.g., in cases wheresubstantially every molecule in a sample is tagged with a differentsequence, and then the sample is amplified). A barcode sequence may beat the 5′-end, the 3′-end or in the middle of an oligonucleotide.Barcode sequences may vary widely in size and composition; the followingreferences provide guidance for selecting sets of barcode sequencesappropriate for particular embodiments: Brenner, U.S. Pat. No.5,635,400; Brenner et al, Proc. Natl. Acad. Sci., 97: 1665-1670 (2000);Shoemaker et al, Nature Genetics, 14: 450-456 (1996); Morris et al,European patent publication 0799897A1; Wallace, U.S. Pat. No. 5,981,179;and the like. In particular embodiments, a barcode sequence may have alength in range of from 4 to 36 nucleotides, or from 6 to 30nucleotides, or from 8 to 20 nucleotides.

The term “in vitro” refers to a reaction that occurs in a vessel withisolated components, not in cells.

The term “distributed” in the context of cleavage sites that aredistributed along the length of a target nucleic acid molecule, refersto insertions that are spaced from another along the length of thetarget nucleic acid molecule. There is no requirement that all of theinsertions are spaced by the same amount. Rather, spacing betweeninsertions may be random, semi-random, or not random.

The term “chromatin,” as used herein, refers to a complex of moleculesincluding proteins and polynucleotides (e.g. DNA, RNA), as found in anucleus of a eukaryotic cell. Chromatin is composed in part of histoneproteins that form nucleosomes, genomic DNA, and other DNA bindingproteins (e.g., transcription factors) that are generally bound to thegenomic DNA.

The term “treating,” as used herein, refers to combining underconditions (e.g., a suitable temperature, time and conditions) thatresult in a reaction, e.g., cleavage.

The term “chromatin isolated from a population of cells,” as usedherein, refers to a source of chromatin that is caused to be madeavailable. Isolated nuclei (which can be lysed to produce chromatin) aswell as isolated chromatin (i.e., the product of lysed nuclei) are bothconsidered types of chromatin isolated from a population of cells.

The term “transcription factor”, as used herein, refers to anypolypeptide that may act by itself or in combination with at least oneother polypeptide to regulate gene expression levels. The term includes,but is not limited to, polypeptides that directly bind DNA sequences.Transcription factors can either increases or suppress expressionlevels. Examples of transcription factors include, but are not limitedto Myc/Max, AP-1 (Jun, Fos, ATF), CREB, SMAD, HIF, ETS, ERG, ELK, STAT,estrogen receptor (ER), androgen receptor (AR), glucocorticoid receptor(GR), progesterone receptor (PR), NFκB, p53, OCT, SOX and PAX. Thetranscription factor may be a transcription factor identified bysequence analysis or a naturally-occurring reading frame sequence thathas not been previously characterized as a transcription factor. Thepolypeptide may also be an artificially generated or chemically orenzymatically modified polypeptide.

The term “insertional enzyme complex,” as used herein, refers to acomplex comprising an insertional enzyme and two adaptor molecules (the“transposon tags”) that are combined with polynucleotides to fragmentand add adaptors to the polynucleotides. Such a system is described in avariety of publications, including Caruccio (Methods Mol. Biol. 2011733: 241-55) and US20100120098, which are incorporated by referenceherein.

The term “tagged fragments,” as used herein, refers to polynucleotidefragments that are attached to tags.

The term “region,” as used herein, refers to a contiguous length ofnucleotides in a genome of an organism. A chromosomal region may be inthe range of 1 bp to the length of an entire chromosome. In someinstances, a region may have a length of at least 200 bp, at least 500bp, at least 1 kb, at least 10 kb or at least 100 kb or more (e.g., upto 1 Mb or 10 Mb or more). The genome may be from any eukaryoticorganism, e.g., an animal or plant genome such as the genome of a human,monkey, rat, fish or insect.

The term “epigenetic map,” as used herein, refers to any representationof epigenetic features, e.g., sites of nucleosomes, nucleosome-freeregions, binding sites for transcription factors, etc. A map can bephysically displayed, e.g., on a computer monitor. Exemplary epigeneticmaps are shown in FIGS. 1C, 3A, 4A, 4B, 5B and 5C.

The term “mapping information,” as used herein, refers to assemblingexperimentally-obtained information about an area to a physical map ofthe area.

The term “sequence read abundance,” as used herein, refers to the numberof times a particular sequence or nucleotide is observed in a collectionof sequence reads.

The term “nucleosome-free fragments,” as used herein, refers tofragments of genomic DNA that are relatively depleted or devoid ofnucleosomes, i.e., between nucleosomes.

The term “chromatin accessibility,” as used herein, refers to howaccessible a nucleic acid site is within a polynucleotide, such as ingenomic DNA, i.e., how “open” the chromatin is. A nucleic acid siteassociated with a polypeptide, such as with genomic DNA in nucleosomes,is usually inaccessible. A nucleic acid site not complexed with apolypeptide is generally accessible, such as with genomic DNA betweennucleosomes (with the exception of nucleic acid sites complexed withtranscription factors and other DNA binding proteins).

The term “DNA binding protein occupancy,” as used herein, refers towhether a binding site for a sequence specific DNA binding protein(e.g., a binding site for a transcription factor) is occupied by the DNAbinding protein. DNA binding protein occupancy can be measuredquantitatively or qualitatively.

The term “global occupancy,” as used herein, refers to whether aplurality of different binding sites for a DNA binding protein that aredistributed throughout the genome (e.g., a binding sites for atranscription factor) are bound by the DNA binding protein. DNA bindingprotein occupancy can be measured quantitatively or qualitatively.

The term “diagnosis,” as used herein, refers to a determination ofwhether a subject has a particular disease or condition.

The term “prognosis,” as used herein, refers to prediction of a clinicaloutcome, e.g., disease recurrence, recovery from a disease, death, aswell as a prediction of how a subject that has a particular disease orcondition will respond to a particular treatment.

Other definitions of terms may appear throughout the specification.

Description of Exemplary Embodiments

In one aspect, a method for analyzing chromatin is provided. In certainembodiments, the method comprises: (a) treating chromatin isolated froma population of cells with an insertional enzyme complex to producetagged fragments of genomic DNA. In this step, the chromatin istagmented (i.e., cleaved and tagged in the same reaction) using aninsertional enzyme such as Tn5 or MuA that cleaves the genomic DNA inopen regions in the chromatin and adds adaptors to both ends of thefragments. Methods for tagmenting isolated genomic DNA are known in theart (see, e.g., Caruccio Methods Mol. Biol. 2011 733: 241-55; Kaper etal, Proc. Natl. Acad. Sci. 2013 110: 5552-7; Marine et al, Appl.Environ. Microbiol. 2011 77: 8071-9 and US20100120098) and arecommercially available from Illumina (San Diego, Calif.) and othervendors. Such systems may be readily adapted for use herein. In somecases, the conditions may be adjusted to obtain a desirable level ofinsertion in the chromatin (e.g., an insertion that occurs, on average,every 50 to 200 base pairs in open regions). The chromatin used in themethod may be made by any suitable method. In some embodiments, nucleimay be isolated, lysed, and the chromatin may be further purified, e.g.,from the nuclear envelope. In other embodiments, the chromatin may beisolated by contacting isolated nuclei with the reaction buffer. Inthese embodiments, the isolated nuclei may lyse when it makes contactwith the reaction buffer (which comprises insertional enzyme complexesand other necessary reagents), which allows the insertional enzymecomplexes access to the chromatin. In these embodiments, the method maycomprise isolating nuclei from a population of cells; and combining theisolated nuclei with the transposase and adaptors, wherein the combiningresults in both lysis of the nuclei to release said chromatin andproduction of the adaptor-tagged fragments of genomic DNA. The chromatindoes not require cross-linking as in other methods (e.g., ChIP-SEQmethods).

After the chromatin has been fragmented and tagged to produce taggedfragments of genomic DNA, at least some of the adaptor tagged fragmentsare sequenced to produce a plurality of sequence reads. The fragmentsmay be sequenced using any convenient method. For example, the fragmentsmay be sequenced using Illumina's reversible terminator method, Roche'spyrosequencing method (454), Life Technologies' sequencing by ligation(the SOLiD platform) or Life Technologies' Ion Torrent platform.Examples of such methods are described in the following references:Margulies et al (Nature 2005 437: 376-80); Ronaghi et al (AnalyticalBiochemistry 1996 242: 84-9); Shendure et al (Science 2005 309:1728-32); Imelfort et al (Brief Bioinform. 2009 10:609-18); Fox et al(Methods Mol Biol. 2009; 553:79-108); Appleby et al (Methods Mol Biol.2009; 513:19-39) and Morozova et al (Genomics. 2008 92:255-64), whichare incorporated by reference for the general descriptions of themethods and the particular steps of the methods, including all startingproducts, methods for library preparation, reagents, and final productsfor each of the steps. As would be apparent, forward and reversesequencing primer sites that are compatible with a selected nextgeneration sequencing platform can be added to the ends of the fragmentsduring the amplification step. In certain embodiments, the fragments maybe amplified using PCR primers that hybridize to the tags that have beenadded to the fragments, where the primer used for PCR have 5′ tails thatare compatible with a particular sequencing platform. In certain cases,the primers used may contain a molecular barcode (an “index”) so thatdifferent pools can be pooled together before sequencing, and thesequence reads can be traced to a particular sample using the barcodesequence.

In another aspect, the present disclosure provides a method fordetermining accessibility of a polynucleotide at a site, wherein thepolynucleotide is from a cell sample, said method comprising: insertinga plurality of molecular tags with an insertional enzyme into thepolynucleotide and using the molecular tags to determine accessibilityat the site. The cell sample can be from a primary source. The cellsample may consist of a single cell. The cell sample may consist of afinite number of cells (e.g. less than about 500,000 cells).

The method can further comprise using the determined accessibility toidentify one or more proteins that are bound to the polynucleotide atthe site. In some instances, at least one of the proteins is atranscription factor. Additionally, the method can comprise using themolecular tags to generate an accessibility map of the polynucleotide.

The polynucleotide may be fragmented into a plurality of fragmentsduring the insertion of the molecular tags. In some cases, the fragmentsmay be amplified. In some cases, the fragments can be sequenced togenerate a plurality of sequencing reads. This may be used to determinethe accessibility of the polynucleotide at any given site. The fragmentsmay be sequenced using a high-throughput sequencing technique. In somecases, the sequencing reads can be normalized based on the sequenceinsertion preference of the insertional enzyme. The length of thesequenced reads can be used to determine a chromatin state annotation.

The polynucleotide can be bound to a plurality of association molecules.The association molecules can be, for example, proteins, nucleic acidsor saccharides. In some cases, the association molecules can comprisehistones. In other cases, the association molecules can compriseaptamers.

The insertional enzyme can be any enzyme capable of inserting a nucleicacid sequence into a polynucleotide. In some cases, the insertionalenzyme can insert the nucleic acid sequence into the polynucleotide in asubstantially sequence-independent manner. The insertional enzyme can beprokaryotic or eukaryotic. Examples of insertional enzymes include, butare not limited to, transposases, HERMES, and HIV integrase. Thetransposase can be a Tn transposase (e.g. Tn3, Tn5, Tn7, Tn10, Tn552,Tn903), a MuA transposase, a Vibhar transposase (e.g. from Vibrioharveyi), Ac-Ds, Ascot-1, Bs1, Cin4, Copia, En/Spm, F element, hobo,Hsmar1, Hsmar2, IN (HIV), IS1, IS2, IS3, IS4, IS5, IS6, IS10, IS21,IS30, IS50, IS51, IS150, IS256, IS407, IS427, IS630, IS903, IS911,IS982, IS1031, ISL2, L1, Mariner, P element, Tam3, Tc1, Tc3, Tel, THE-1,Tn/O, TnA, Tn3, Tn5, Tn7, Tn10, Tn552, Tn903, To11, To12, Tn10, Ty1, anyprokaryotic transposase, or any transposase related to and/or derivedfrom those listed above. In certain instances, a transposase related toand/or derived from a parent transposase can comprise a peptide fragmentwith at least about 50%, about 55%, about 60%, about 65%, about 70%,about 75%, about 80%, about 85%, about 90%, about 91%, about 92%, about93%, about 94%, about 95%, about 96%, about 97%, about 98%, or about 99%amino acid sequence homology to a corresponding peptide fragment of theparent transposase. The peptide fragment can be at least about 10, about15, about 20, about 25, about 30, about 35, about 40, about 45, about50, about 60, about 70, about 80, about 90, about 100, about 150, about200, about 250, about 300, about 400, or about 500 amino acids inlength. For example, a transposase derived from Tn5 can comprise apeptide fragment that is 50 amino acids in length and about 80%homologous to a corresponding fragment in a parent Tn5 transposase. Insome cases, the insertion can be facilitated and/or triggered byaddition of one or more cations. The cations can be divalent cationssuch as, for example, Ca²⁺, Mg²⁺ and Mn²⁺.

The molecular tags can comprise sequencing adaptors, locked nucleicacids (LNAs), zip nucleic acids (ZNAs), RNAs, affinity reactivemolecules (e.g. biotin, dig), self-complementary molecules,phosphorothioate modifications, azide or alkyne groups. In some cases,the sequencing adaptors can further comprise a barcode label. Further,the barcode labels can comprises a unique sequence. The unique sequencescan be used to identify the individual insertion events. Any of the tagscan further comprise fluorescence tags (e.g. fluorescein, rhodamine,Cy3, Cy5, thiazole orange, etc.).

Additionally, the insertional enzyme can further comprise an affinitytag. In some cases, the affinity tag can be an antibody. The antibodycan bind to, for example, a transcription factor, a modified nucleosomeor a modified nucleic acid. Examples of modified nucleic acids include,but are not limited to, methylated or hydroxymethylated DNA. In othercases, the affinity tag can be a single-stranded nucleic acid (e.g.ssDNA, ssRNA). In some examples, the single-stranded nucleic acid canbind to a target nucleic acid. In further cases, the insertional enzymecan further comprise a nuclear localization signal.

In some cases, the cell sample can be permeabilized to allow access forthe insertional enzyme. The permeabilization can be performed in a wayto minimally perturb the nuclei in the cell sample. In some instances,the cell sample can be permeabilized using a permeabilization agent.Examples of permeabilization agents include, but are not limited to,NP40, digitonin, tween, streptolysin, and cationic lipids. In otherinstances, the cell sample can be permeabilized using hypotonic shockand/or ultrasonication. In other cases, the insertional enzyme can behighly charged, which may allow it to permeabilize through cellmembranes.

In yet another aspect, the present disclosure provides a method foranalyzing the three-dimensional structure of a polynucleotide from acell sample, comprising: inserting a plurality of molecular tags with aninsertional enzyme into the polynucleotide; and using the molecular tagsto analyze the three-dimensional structure of the polynucleotide. Theinsertional enzyme can comprise two or more enzymatic moieties, whichmay be optionally linked together. The enzymatic moieties can be linkedby using any suitable chemical synthesis or bioconjugation methods. Forexample, the enzymatic moieties can be linked via an ester/amide bond, athiol addition into a maleimide, Native Chemical Ligation (NCL)techniques, Click Chemistry (i.e. an alkyne-azide pair), or abiotin-streptavidin pair. In some cases, each of the enzymatic moietiescan insert a common sequence into the polynucleotide. The commonsequence can comprise a common barcode. The enzymatic moieties cancomprise transposases or derivatives thereof. In some embodiments, thepolynucleotide may be fragmented into a plurality of fragments duringthe insertion. The fragments comprising the common barcode can bedetermined to be in proximity in the three-dimensional structure of thepolynucleotide.

The polynucleotide can be genomic DNA. The polynucleotide can be furtherbound to proteins, such as histones, and may be optionally packaged inthe form of chromatin. In particular cases, DNA fragments correspondingto one or more regions of a genome (e.g., 2 or more, 10 or more, 50 ormore, 100 or more, up to 1,000 or more regions) may be enriched, i.e.,selected, by hybridization prior to sequencing. In these embodiments,the entire library does not need to be sequenced. Depending on thedesired result and length of the selected region (if a selection stephas been performed), this step of the method may result in at least1,000 sequencing (e.g., at least 10,000, at least 100,000, at least500,000, at least 10⁶, at least 5×10⁶, up to 10⁷ or more sequencingreads). The sequence reads are generally stored in computer memory.

Some embodiments of the methods involve making an epigenetic map of aregion of the genome of the cells. This step may be done by mappinginformation obtained from the sequence reads to the region. In theseembodiments, the sequence reads are analyzed computationally to producea number of numerical outputs that are mapped to a representation (e.g.,a graphical representation) of a region of interest. As will beexplained in greater detail below, many types of information may bemapped, including, but not limited to: (i) cleavage sites for thetransposase; (ii) the sizes of the fragments produced in step a); (iii)fragment length; (iii) the positions of sequence reads of a definedrange in length; and (iv) sequence read abundance.

For example, the sequence reads may be analyzed computationally toidentify the ends of the fragments (from which the transposon cleavagesites can be inferred). In these embodiments, one end of a fragment canbe defined by sequence that is at the beginning of a sequencing read andthe other end of the fragment can be defined by sequence that is at thebeginning of a second sequencing read, where the first and secondsequencing reads were obtained by paired end sequencing (e.g., usingIllumina's sequencing platform). The same information can be obtainedfrom examining the beginning and end of longer sequence reads (whichshould, in theory, have the sequence of both adaptors; one at one endand the other at the other end). In these embodiments, a single sequenceread may contain both adaptor sequences, in which case both ends of afragment (which correspond to two cleavage sites for the two separatetransposases) can be inferred from a single sequence read. The lengthsof the fragments can be calculated by, e.g., mapping the fragment endsonto the nucleotide sequence of the region of interest, and counting thenumber of base pairs between those positions. The information used maybe obtained using the nucleotide sequences at the beginning and/or theend of a sequence read.

In certain cases, the sequence reads can be placed into groups bylength. In some embodiments, some sequences can be annotated as being anucleosome-free sequence (i.e., a sequence from a fragment that ispredicted to be between nucleosomes) based on its size. Reads that areassociated with mononucleosomes, dinucleosomes and trinucleosomes canalso be identified. These cutoffs can be determined using the data shownin FIG. 12. Fragment lengths (which provide the same information assequence read lengths) can also be processed in the same way. In certaincases, sequence read abundance, i.e., the number of times a particularsequence in a genomic region is represented in the sequence reads, maybe calculated.

The resultant epigenetic map can provide an analysis of the chromatin inthe region of interest. For example, depending on which information ismapped, the map can show one or more of the following: a profile ofchromatin accessibility along the region; DNA binding protein (e.g.,transcription factor) occupancy for a site in the region;nucleosome-free DNA in the region; positioning of nucleosomes along theregion; and a profile of chromatin states along the region. In someembodiments, the method may further comprise measuring global occupancyof a binding site for the DNA binding protein by, e.g., aggregating datafor one DNA binding protein over a plurality of sites to which thatprotein binds. In certain instances, the map can also be annotated withsequence information, and information about the sequence (e.g., thepositions of promoters, introns, exons, known enhancers, transcriptionalstart sites, untranslated regions, terminators, etc.) so that theepigenetic information can be viewed in context with the annotation.

In certain embodiments, the epigenetic map can provide informationregarding active regulatory regions and/or the transcription factorsthat are bound to the regulatory regions. For example, nucleosomepositions can be inferred from the lengths of sequencing readsgenerated. Alternatively, transcription factor binding sites can beinferred from the size, distribution and/or position of the sequencingreads generated. In some cases, novel transcription factor binding sitescan be inferred from sequencing reads generated. In other cases, noveltranscription factors can be inferred from sequencing reads generated.

The population of cells used in the assay may be composed of any numberof cells, e.g., about 500 to about 10⁶ or more cells, about 500 to about100,000 cells, about 500 to about 50,000 cells, about 500 to about10,000 cells, about 50 to 1000 cells, about 1 to 500 cells, about 1 to100 cells, about 1 to 50 cells, or a single cell. In some cases, thecell sample can consist of less than about 1000, about 2000, about 3000,about 4000, about 5000, about 6000, about 7000, about 8000, about 9000,about 10,000, about 15,000, about 20,000, about 25,000, about 30,000,about 40,000, about 50,000, about 60,000, about 70,000, about 80,000,about 90,000, about 100,000, about 120,000, about 140,000, about160,000, about 180,000, about 200,000, about 250,000, about 300,000,about 350,000, about 400,000, about 450,000, about 500,000, about600,000, about 700,000, about 800,000, about 900,000, or about 1,000,000cells. In other cases, the cell sample can consist of more than about1000, about 2000, about 3000, about 4000, about 5000, about 6000, about7000, about 8000, about 9000, about 10,000, about 15,000, about 20,000,about 25,000, about 30,000, about 40,000, about 50,000, about 60,000,about 70,000, about 80,000, about 90,000, about 100,000, about 120,000,about 140,000, about 160,000, about 180,000, about 200,000, about250,000, about 300,000, about 350,000, about 400,000, about 450,000,about 500,000, about 600,000, about 700,000, about 800,000, about900,000, or about 1,000,000 cells.

The cells can be from any source. In certain cases, the cells may beobtained from a culture of cells, e.g., a cell line. In other cases, thecells may be isolated from an individual (e.g., a patient or the like).The cells may be isolated from a soft tissue or from a bodily fluid, orfrom a cell culture that is grown in vitro. In particular embodiments,the chromatin may be isolated from a soft tissue such as brain, adrenalgland, skin, lung, spleen, kidney, liver, spleen, lymph node, bonemarrow, bladder stomach, small intestine, large intestine or muscle,etc. Bodily fluids include blood, plasma, saliva, mucous, phlegm,cerebral spinal fluid, pleural fluid, tears, lactal duct fluid, lymph,sputum, cerebrospinal fluid, synovial fluid, urine, amniotic fluid, andsemen, etc.

In some embodiments, the polynucleotide (e.g. genomic DNA, chromosomalDNA) used in the method may be from blood cells, wherein blood cellsrefers to a sample of whole blood or a sub-population of cells in wholeblood. Sub-populations of cells in whole blood include platelets, redblood cells (erythrocytes), platelets and white blood cells (i.e.,peripheral blood leukocytes, which are made up of neutrophils,lymphocytes, eosinophils, basophils and monocytes). These five types ofwhite blood cells can be further divided into two groups, granulocytes(which are also known as polymorphonuclear leukocytes and includeneutrophils, eosinophils and basophils) and mononuclear leukocytes(which include monocytes and lymphocytes). Lymphocytes can be furtherdivided into T cells, B cells and NK cells. Peripheral blood cells arefound in the circulating pool of blood and not sequestered within thelymphatic system, spleen, liver, or bone marrow. Other cells are presentin blood that can be isolated. If blood is first contacted with an agentand then a sample of the blood is used in an assay, then a portion orall of the contacted blood may be used in the assay.

In certain embodiments, the cell sample can be isolated directly from aprimary source. For example, the cell sample can be isolated directlyfrom fresh tissues. In other cases, the cell sample can be isolateddirectly from frozen tissues. In yet other cases, the cell sample can beisolated directly from fixed tissues. Further examples of primarysources of cell samples include, but are not limited to, cellsdissociated from tissues, blood cells, FFPE tissues, bacterial, viral,mitochondria, chloroplast, in vitro assembled protein DNA complexes,neutrophil extracellular traps.

Using the methods provided in the present disclosure, the disease statein a subject can be analyzed based on the accessibility of apolynucleotide site in a cell sample obtained from the subject. Forexample, transcription factor occupancy at any given site can result inthe lack of accessibility at the site. Based on the transcription factoroccupancy, the subject can then be treated with a suitable agent (e.g. atranscription factor inhibitor).

In certain cases, the cell samples can be further analyzedphenotypically. For example, the cell samples can be analyzed usingfluorescence activated cell sorting (FACS) and/or laser capturemicrodissection (LCM). In some cases, the cell sample and/orpolynucleotides may be divided into a plurality of portions. Theportions can be divided based on the molecular tags (e.g. fluorescencetags). In some cases, the cell sample and/or polynucleotides can besorted. The sorting can be performed after the molecular tags areinserted into the polynucleotide. The sorting can be performed beforethe fragments are sequenced. The gene transcription of the cell samplescan also be analyzed using techniques such as fluorescence in situhybridization (FISH). The chromatin accessibility can be correlated withthe phenotypical, transcriptional or translational analysis.

In some embodiments, the cells are of the same cell type. In theseembodiments, the population of cells may be selected by MACS or FACSfrom a heterogeneous population of cells, e.g., blood, by known methodsusing labeled antibodies to cells surface markers. A wide variety ofcells can be isolated using these methods, including stem cells, cancerstem cells and subsets of blood cells. In particular embodiments thefollowing cells may be isolated from blood by FACS or MACS; T cells(CD3⁺ CD4⁺ CD8⁺), B cells (CD19⁺ CD20⁺), dendritic cells (CD11c⁺ CD20⁺),NK Cell (CD56⁺), stem cells/precursor cells (CD34⁺; hematopoietic stemcells only), macrophage/monocytes (CD14⁺ CD33⁺), granulocytes (CD66b⁺),platelet (CD41⁺ CD61⁺ CD62⁺), erythrocytes (CD235a⁺), endothelial cells(CD146⁺) and epithelial cells (CD326⁺). Subsets of these cells can beisolated using antibodies to further cell surface markers.

In some embodiments, the method can be used to compare two samples. Inthese embodiments, the method may comprise analyzing a first populationof cells using the above-described method to produce a first epigeneticmap; and analyzing a second population of cells using theabove-described method to produce a second epigenetic map; and comparingthe first epigenetic map to the second epigenetic map, e.g., to see ifthere are any changes in chromatin openness or transcription factoroccupancy, for example.

In some embodiments, the first population of cells and the secondpopulation of cells are collected from the same individual at differenttimes. In other embodiments, the first population of cells and thesecond population of cells are different populations of cells collectedfrom tissues or different individuals.

Exemplary cell types that can be used in the method include, forexample, cells isolated from a tissue biopsy (e.g., from a tissue havinga disease such as colon, breast, prostate, lung, skin cancer, orinfected with a pathogen etc.) and normal cells from the same tissue,e.g., from the same patient; cells grown in tissue culture that areimmortal (e.g., cells with a proliferative mutation or an immortalizingtransgene), infected with a pathogen, or treated (e.g., withenvironmental or chemical agents such as peptides, hormones, alteredtemperature, growth condition, physical stress, cellular transformation,etc.), and normal cells (e.g., cells that are otherwise identical to theexperimental cells except that they are not immortalized, infected, ortreated, etc.); cells isolated from a mammal with a cancer, a disease, ageriatric mammal, or a mammal exposed to a condition, and cells from amammal of the same species, e.g., from the same family, that is healthyor young; and differentiated cells and non-differentiated cells from thesame mammal (e.g., one cell being the progenitor of the other in amammal, for example). In one embodiment, cells of different types, e.g.,neuronal and non-neuronal cells, or cells of different status (e.g.,before and after a stimulus on the cells) may be compared. In anotherembodiment, the experimental material is cells susceptible to infectionby a pathogen such as a virus, e.g., human immunodeficiency virus (HIV),etc., and the control material is cells resistant to infection by thepathogen. In another embodiment of the invention, the sample pair isrepresented by undifferentiated cells, e.g., stem cells, anddifferentiated cells. Cells from yeast, plants and animals, such asfish, birds, reptiles, amphibians and mammals may be used in the subjectmethods. In certain embodiments, mammalian cells, i.e., cells from mice,rabbits, primates, or humans, or cultured derivatives thereof, may beused.

In some exemplary embodiments, the method may be used to identify theeffect of a test agent, e.g., a drug, or to determine if there aredifferences in the effect of two or more different test agents. In theseembodiments, two or more identical populations of cells may be preparedand, depending on how the experiment is to be performed, one or more ofthe populations of cells may be incubated with the test agent for adefined period of time. After incubation with the test agent, thechromatin of the populations of cells can be analyzed using the methodsset forth above, and the results can be compared. In a particularembodiment, the cells may be blood cells, and the cells can be incubatedwith the test agent ex vivo. These methods can be used to determine themode of action of a test agent, to identify changes in chromatinstructure or transcription factor occupancy in response to the drug, forexample.

The method described above may also be used as a diagnostic (which termis intended to include methods that provide a diagnosis as well asmethods that provide a prognosis). These methods may comprise, e.g.,analyzing chromatin from a patient using the method described above toproduce an epigenetic map; and providing a diagnosis or prognosis basedon the epigenetic map.

The method set forth herein may be used to provide a reliable diagnosticto any condition associated with altered chromatin or DNA bindingprotein occupancy. The method can be applied to the characterization,classification, differentiation, grading, staging, diagnosis, orprognosis of a condition characterized by an epigenetic pattern (e.g., apattern of chromatin accessibility or DNA binding protein occupancy).For example, the method can be used to determine whether the epigeneticmap of a sample from an individual suspected of being affected by adisease or condition is the same or different compared to a sample thatis considered “normal” with respect to the disease or condition. Inparticular embodiments, the method can be directed to diagnosing anindividual with a condition that is characterized by an epigeneticpattern at a particular locus in a test sample, where the pattern iscorrelated with the condition. The methods can also be used forpredicting the susceptibility of an individual to a condition.

Exemplary conditions that are suitable for analysis using the methodsset forth herein can be, for example, cell proliferative disorder orpredisposition to cell proliferative disorder; metabolic malfunction ordisorder; immune malfunction, damage or disorder; CNS malfunction,damage or disease; symptoms of aggression or behavioral disturbance;clinical, psychological and social consequences of brain damage;psychotic disturbance and personality disorder; dementia or associatedsyndrome; cardiovascular disease, malfunction and damage; malfunction,damage or disease of the gastrointestinal tract; malfunction, damage ordisease of the respiratory system; lesion, inflammation, infection,immunity and/or convalescence; malfunction, damage or disease of thebody as an abnormality in the development process; malfunction, damageor disease of the skin, the muscles, the connective tissue or the bones;endocrine and metabolic malfunction, damage or disease; headache orsexual malfunction, and combinations thereof.

In some embodiments, the method can provide a prognosis, e.g., todetermine if a patient is at risk for recurrence. Cancer recurrence is aconcern relating to a variety of types of cancer. The prognostic methodcan be used to identify surgically treated patients likely to experiencecancer recurrence so that they can be offered additional therapeuticoptions, including preoperative or postoperative adjuncts such aschemotherapy, radiation, biological modifiers and other suitabletherapies. The methods are especially effective for determining the riskof metastasis in patients who demonstrate no measurable metastasis atthe time of examination or surgery.

The method can also be used to determining a proper course of treatmentfor a patient having a disease or condition, e.g., a patient that hascancer. A course of treatment refers to the therapeutic measures takenfor a patient after diagnosis or after treatment. For example, adetermination of the likelihood for recurrence, spread, or patientsurvival, can assist in determining whether a more conservative or moreradical approach to therapy should be taken, or whether treatmentmodalities should be combined. For example, when cancer recurrence islikely, it can be advantageous to precede or follow surgical treatmentwith chemotherapy, radiation, immunotherapy, biological modifiertherapy, gene therapy, vaccines, and the like, or adjust the span oftime during which the patient is treated.

In a particular embodiment, a lab will receive a sample (e.g., blood)from a remote location (e.g., a physician's office or hospital), the labwill analyze cells in the sample as described above to produce data, andthe data may be forwarded to the remote location for analysis.

Compositions

In one aspect, the present disclosure provides compositions related tothe methods provided herein. The composition can comprise apolynucleotide, an insertional enzyme and an insert element, wherein:the insert element can comprise a nucleic acid comprising apredetermined sequence and the insertional enzyme can further comprisean affinity tag. The polynucleotide can be further bound to a pluralityof association molecules. The association molecules can be proteins(e.g. histones) or nucleic acids (e.g. aptamers). The affinity tag canbe an antibody. In some cases, the antibody can be bound to atranscription factor. In other cases, the antibody can be bound to amodified nucleosome. In further cases, the antibody can be bound to amodified nucleic acid. Examples of modified nucleic acids include, butare not limited to, methylated or hydroxymethylated DNA. The affinitytag can also be a single-stranded nucleic acid (e.g. ssDNA, ssRNA). Insome cases, the single-stranded nucleic acid can be bound to a targetnucleic acid. In some instances, the insertional enzyme can furthercomprise a nuclear localization signal.

The composition can comprise a polynucleotide, an insertional enzyme andan insert element, wherein: the insertional enzyme comprises two or moreenzymatic moieties and the enzymatic moieties are linked together. Theinsert element can be bound to the insertional enzyme. The insertionalenzyme can also be bound to the polynucleotide. In some cases, thepolynucleotide can be further bound to a plurality of associationmolecules. The association molecules can be proteins (e.g. histones) ornucleic acids (e.g. aptamers).

Kits

In yet another aspect, the present disclosure provides kits that containreagents for practicing the subject methods, as described above. Thesubject kits can comprise: (a) reagents for isolating nuclei from apopulation of cells; (b) transposase and transposon tags, and (c)transposase reaction buffer, wherein the components of the kit areconfigured such that, combining the reaction buffer, transposase andadaptors with nuclei in vitro results in both lysis of the nuclei torelease chromatin and production of adaptor-tagged fragments of genomicDNA.

In some cases, the kit can comprise: (a) a cell lysis buffer; (b) aninsertional enzyme comprising an affinity tag; and (c) an insert elementcomprising a nucleic acid, wherein said nucleic acid comprises apredetermined sequence. The insertional enzyme can be, for example, atransposase. The insertional enzyme can also comprise two or moreenzymatic moieties that are linked together. In some cases, the affinitytag can be an antibody. The antibody can bind to a transcription factor,a modified nucleosome, or a modified nucleic acid. Examples of modifiednucleic acids include, but are not limited to, methylated orhydroxymethylated DNA. In other cases, the affinity tag can be asingle-stranded nucleic acid (e.g. ssDNA, ssRNA).

The kit may optionally contain other components, for example: PCRprimers, PCR reagents such as polymerase, buffer, nucleotides etc., asdescribed above. The various components of the kit may be present inseparate containers or certain compatible components may be precombinedinto a single container, as desired.

In addition to above-mentioned components, the subject kits may furtherinclude instructions for using the components of the kit to practice thesubject methods, i.e., instructions for sample analysis. Theinstructions for practicing the subject methods are generally recordedon a suitable recording medium. For example, the instructions may beprinted on a substrate, such as paper or plastic, etc. As such, theinstructions may be present in the kits as a package insert, in thelabeling of the container of the kit or components thereof (i.e.,associated with the packaging or subpackaging) etc. In otherembodiments, the instructions are present as an electronic storage datafile present on a suitable computer readable storage medium, e.g.,CD-ROM, diskette, etc. In yet other embodiments, the actual instructionsare not present in the kit, but means for obtaining the instructionsfrom a remote source, e.g., via the internet, are provided. An exampleof this embodiment is a kit that includes a web address where theinstructions can be viewed and/or from which the instructions can bedownloaded. As with the instructions, this means for obtaining theinstructions is recorded on a suitable substrate.

Embodiments

A method of mapping chromatin is provided. In some embodiments, thismethod comprises the steps of: fragmenting the chromatin of rare orabundant cells with a transposase which inserts sequencing adapters intothe polynucleotides within the chromatin, and amplifying and sequencingthe fragments to generate a cell-specific map.

In certain embodiments, the cell-specific map provides informationregarding active regulatory regions and the transcription factors thatare bound to said regulatory regions.

In certain embodiments, the number of said rare cells is between 1 and100,000.

In certain embodiments, the transposase is derived from Tn5 transposase.

In certain embodiments, the transposase is derived from MuA transposase.

In certain embodiments, nucleosome positions are inferred from thelengths of sequencing reads generated.

In certain embodiments, transcription factor binding sites are inferredfrom sequencing reads generated.

In certain embodiments, chromatin is isolated directly from freshtissues.

In certain embodiments, chromatin is isolated directly from frozentissues.

In certain embodiments, chromatin is isolated directly from fixedtissues.

In certain embodiments, sequences are added to the sequencing adapter touniquely identify the fragments for multiplexing (barcoding).

In certain embodiments, an affinity tag is used to target thetransposase to a specific macromolecule of interest.

In certain embodiments, sequences are added to the sequencing adapter touniquely identify the fragments for multiplexing (barcoding), and anaffinity tag is used to target the transposase to a specificmacromolecule of interest.

In certain embodiments the affinity tag is an antibody targeted to atranscription factor.

In certain embodiments the affinity tag is an antibody targeted to amodified nucleosome.

In certain embodiments, the insert size distribution at a specificgenomic locus is used to infer chromatin openness.

In certain embodiments, the insert size distribution and positions ofinsertion are used to infer transcription factor binding.

In certain embodiments, the number of sequencing reads obtained isnormalized by measured sequence insertion preference of the transposase.

In certain embodiments, novel transcription factor binding sites areinferred from sequencing reads generated.

In certain embodiments, novel transcription factors are inferred fromsequencing reads generated.

In certain embodiments, causal variants can be inferred by looking atallele specific generation of sequencing reads.

In certain embodiments, chromatin state annotations are inferred fromthe distribution of lengths of sequencing reads.

EXAMPLES

Aspects of the present teachings can be further understood in light ofthe following examples, which should not be construed as limiting thescope of the present teachings in any way.

Example 1 Assay for Transposase Accessible Chromatin using sequencing(ATAC-seq)

Described herein is an Assay for Transposase Accessible Chromatin usingsequencing (ATAC-seq)—based on direct in vitro transposition ofsequencing adapters into native chromatin—as a rapid and sensitivemethod for integrative epigenomic analysis. ATAC-seq captures openchromatin sites using a simple 2-step protocol from 500 to 50,000 cells,and reveals the interplay between genomic locations of open chromatin,DNA binding proteins, individual nucleosomes, and higher-ordercompaction at regulatory regions with nucleotide resolution. Classes ofDNA binding factor that strictly avoid, can tolerate, or tend to overlapwith nucleosomes have been discovered. Using ATAC-seq, the serial dailyepigenomes of resting human T cells was measured and evaluated from aproband via standard blood draws, demonstrating the feasibility ofreading personal epigenomes in clinical timescales for monitoring healthand disease.

Materials and Methods

An exemplary implementation of ATAC-seq protocol has three major steps:

1) Prepare nuclei: To prepare nuclei, 50,000 cells were spun at 500×gfor 5 minutes, followed by a wash using 50 μL of cold lx PBS andcentrifugation at 500×g for 5 minutes. Cells were lysed using cold lysisbuffer (10 mM Tris-Cl, pH 7.4, 10 mM NaCl, 3 mM MgCl₂ and 0.1% IGEPALCA-630). Immediately after lysis, nuclei were spun at 500×g for 10minutes using a refrigerated centrifuge. To avoid losing cells duringthe nuclei prep, a fixed angle centrifuge was used and they werecarefully pipetted away from the pellet after centrifugations.

2) Transpose and purify: Immediately following the nuclei prep, thepellet was resuspended in the transposase reaction mix (25 μL 2× TDbuffer, 2.5 μL Transposase (Illumina) and 22.5 μL of nuclease freewater). The transposition reaction was carried out for 30 minutes at 37°C. Directly following transposition the sample was purified using aQiagen Minelute kit.

3) PCR: Following purification, we amplified library fragments using 1×NEBnext PCR master mix and 1.25 μM of custom Nextera PCR primers 1 and 2(see table below), using the following PCR conditions: 72° C. for 5minutes, 98° C. for 30 seconds, followed by thermocycling at 98° C. for10 seconds, 63° C. for 30 seconds and 72° C. for 1 minute. To reduce GCand size bias in PCR, the PCR reactions were monitored using qPCR inorder to stop amplification prior to saturation. To do this, the fulllibraries were amplified for 5 cycles, after 5 cycles an aliquot of thePCR reaction was taken and added to 10 μl of the PCR cocktail with SybrGreen at a final concentration of 0.6×. We ran this reaction for 20cycles, to determine the additional number of cycles needed for theremaining 45 μL reaction. The libraries were purified using a Qiagen PCRcleanup kit yielding a final library concentration of ˜30 nM in 20 μL.Libraries were amplified for a total of 10-12 cycles.

Ad1_noMX: AATGATACGGCGACCACCGAGAT CTACACTCGTCGGCAGCGTCAGATGTG (SEQ ID NO: 1) Ad2.1_TAAGGCGA CAAGCAGAAGACGGCATACGAGATTCGCCTTAGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 2) Ad2.2_CGTACTAGCAAGCAGAAGACGGCATACGAGA TCTAGTACGGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 3)Ad2.3_AGGCAGAA CAAGCAGAAGACGGCATACGAGA TTTCTGCCTGTCTCGTGGGCTCGGAGATGT (SEQ ID NO: 4) Ad2.4_TCCTGAGC CAAGCAGAAGACGGCATACGAGATGCTCAGGAGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 5) Ad2.5_GGACTCCTCAAGCAGAAGACGGCATACGAGA TAGGAGTCCGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 6)Ad2.6_TAGGCATG CAAGCAGAAGACGGCATACGAGA TCATGCCTAGTCTCGTGGGCTCGGAGATGT (SEQ ID NO: 7) Ad2.7_CTCTCTAC CAAGCAGAAGACGGCATACGAGATGTAGAGAGGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 8) Ad2.8_CAGAGAGGCAAGCAGAAGACGGCATACGAGA TCCTCTCTGGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 9)Ad2.9_GCTACGCT CAAGCAGAAGACGGCATACGAGA TAGCGTAGCGTCTCGTGGGCTCGGAGATGT (SEQ ID NO: 10) Ad2.10_CGAGGCTG CAAGCAGAAGACGGCATACGAGATCAGCCTCGGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 11) Ad2.11_AAGAGGCACAAGCAGAAGACGGCATACGAGA TTGCCTCTTGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 12)Ad2.12_GTAGAGGA CAAGCAGAAGACGGCATACGAGA TTCCTCTACGTCTCGTGGGCTCGGAGATGT (SEQ ID NO: 13) Ad2.13_GTCGTGAT CAAGCAGAAGACGGCATACGAGATATCACGACGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 14) Ad2.14_ACCACTGTCAAGCAGAAGACGGCATACGAGA TACAGTGGTGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 15)Ad2.15_TGGATCTG CAAGCAGAAGACGGCATACGAGA TCAGATCCAGTCTCGTGGGCTCGGAGATGT (SEQ ID NO: 16) Ad2.16_CCGTTTGT CAAGCAGAAGACGGCATACGAGATACAAACGGGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 17) Ad2.17_TGCTGGGTCAAGCAGAAGACGGCATACGAGA TACCCAGCAGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 18)Ad2.18_GAGGGGTT CAAGCAGAAGACGGCATACGAGA TAACCCCTCGTCTCGTGGGCTCGGAGATGT (SEQ ID NO: 19) Ad2.19_AGGTTGGG CAAGCAGAAGACGGCATACGAGATCCCAACCTGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 20) Ad2.20_GTGTGGTGCAAGCAGAAGACGGCATACGAGA TCACCACACGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 21)Ad2.21_TGGGTTTC CAAGCAGAAGACGGCATACGAGA TGAAACCCAGTCTCGTGGGCTCGGAGATGT (SEQ ID NO: 22) Ad2.22_TGGTCACA CAAGCAGAAGACGGCATACGAGATTGTGACCAGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 23) Ad2.23_TTGACCCTCAAGCAGAAGACGGCATACGAGA TAGGGTCAAGTCTCGTGGGCTCG GAGATGT (SEQ ID NO: 24)Ad2.24_CCACTCCT CAAGCAGAAGACGGCATACGAGA TAGGAGTGGGTCTCGTGGGCTCGGAGATGT (SEQ ID NO: 25)

Low cell number protocol: To prepare the 500 and 5,000 cell reactionsthe same protocol was used with some notable exceptions: Thetransposition reaction was done in a 5 μL instead of 50 μL reaction.Also, the Qiagen Minelute purification was eliminated prior to PCR andinstead took the 5 μL reaction immediately after transposition directlyinto the 50 μL PCR.

Library QC and quantitation: During the ATAC-seq protocol, the sizeselection step was avoided to maximize the library complexity. Thesequenced insert size is a distribution between 40 bp to 1 kb with amean of ˜120 bps. From bioanalyzer and gels we observed fragments >2 kb,which would make Qubit and other mass-based quantitation methods hard tointerpret. For this reason we quantified our libraries using qPCR basedmethods.

CD4⁺ enrichment from peripheral blood: One green-top tube of whole bloodwas obtained from 1 normal volunteer three times over a 72-hour period,under a Stanford University IRB-approved protocol. Informed consent wasobtained. 5 mL of blood at each timepoint was negatively selected forCD4+ cells, using RosetteSep Human CD4⁺ T Cell Enrichment Cocktail(StemCell Technology). RosetteSep cocktail was incubated with the bloodat 50 μL/mL for 20 min, diluted in an equal volume of PBS with 2% FBS,and underlayed with 15 mL Ficol-Paque Plus (GE). Blood was centrifugedfor 20 minutes at 1200×g without break, negatively selected cells wereremoved from the density medium: plasma interface, and cells were washedX2 in PBS with 2% FBS.

FACS sorting peripheral blood leukocytes and GM cells: GM 12878 cellswere stained with DAPI NucBlue Fixed Cell Stain (molecular probes) andlive cells were sorted using a FACSAria (BD Biosciences) using a 100 μmnozzle. One peripheral blood sample (buffy coat) was stained with BDBioscience antibodies CD14-A-488 (M5E2, 1:20), CD3-PE-Cy7 (SK7, 1:20),CD4-APC-Cy7 (RPA-T4, 1:20), and CD8 (RPA-T8, 1:20) for 20 minutes in thedark at RT. Cells were lysed using BDpharmLyse 1:10 dil in diH20 (BD)for 15 min, centrifuged for 5 minutes, washed with PBS 2% FBS X 2, andresuspended in PBS with 2% FBS. 50,000 CD3⁺CD8⁺, CD3⁺CD4⁺, and CD14⁺cell populations were sorted into PBS with 10% FBS.

Data Analysis

Primary data processing: Data was collected using either 34×8×34 readsfrom a MiSeq or 50×8×50 reads on a HiSeq. Reads were aligned to hg19using BOWTIE (Langmead et al Genome Biol. 2009 10, R25) using theparameters −X2000 and −m1. These parameters ensured that fragments up to2 kb were allowed to align (−X2000) and that only unique aligning readswere collected (−m1). For all data files duplicates were removed usingPicard.

For peak calling and footprinting, the read start sites were adjusted torepresent the center of the transposon binding event. Previousdescriptions of the Tn5 transposase show that the transposon binds as adimer and inserts two adapters separated by 9 bps (Adey, A. et al.Genome Biol 2010 11: R119). Therefore, all reads aligning to the +strand were offset by +4 bps, and all reads aligning to the − strandwere offset −5 bps.

ATAC-seq peak calling: We used ZINBA to call all reported ATAC-seq peaksin this manuscript. ZINBA was run using a window size of 300 bp and anoffset 75 bp. Alignability was used to model the zero-inflated componentand the ATAC-seq read count for the background and enriched components.Enriched regions were identified as those with a posterior probability>0.8.

ATAC-seq insertion size enrichment analysis within chromatinannotations: First, the distribution of paired-end sequencing fragmentsizes overlapping each chromatin state (see the ensemble.org website)were computed. The distributions were then normalized to the percentmaximal within each state and enrichment was computed relative to thegenome-wide set of fragment sizes.

Nucleosome positioning: To generate the nucleosome position data track,we chose to split reads into various bins. Reads below 100 bps wereconsidered nucleosome free, reads between 180 and 247 bps wereconsidered to be mononucleosomes, reads between 315 and 473 bps wereconsidered to be dinucleosomes and reads between 558 and 615 wereconsidered to be trinucleosomes (for determining cutoffs see FIG. 12).Dinucleosome reads were split into two reads and Trinucleosome readswere split into three reads. Reads were analyzed using Danpos andDantools using the parameters -p 1, -a 1, -d 20, -clonalcut 0. Thebackground used was nucleosome free reads (reads less than 100 bps),allowing an effective negative weighting of these reads. This analysisallows calling multiple overlapping nucleosomes. Although generatingnucleosome tracks using simple insert size cutoffs may yield falsepositives due to other nucleosome sized features, i.e. enhanaceosomes,we observed that we faithfully recapitulated global features onnucleosome position genome-wide (FIG. 2c,d main text).

ChIP-seq peak calling and clustering: ChIP-seq data was downloaded fromthe UCSC ENCODE repository. Peaks where called using GEM (Guo et al,PLoS Comput. Biol. 2012 8: e1002638), the parameters used where −k_min6−k_max 20. Inputs where used as a control for peak calling. Bindingevents were annotated by distance to the nearest dyad in bins of 10 bps.Factors were then hierarchically clustered using Euclidean distance andnormalized by gene and centered by mean. (Eisen et al. Proc. Natl. Acad.Sci. 1998 95: 14863-14868).

Footprinting using CENTIPEDE: The genome-wide set of motifs wereobtained from the ENCODE motif repository (at the website ofbroadinstitute.org). The input for CENTIPEDE included the PWM score,conservation (PhyloP) and ATAC-seq counts within +/−100 bp of eachgenomic region matching a motif. ChIP-seq data was obtained from theUCSC ENCODE repository.

Comparison of transcription factor regulatory networks: Transcriptionfactor regulatory networks were constructed by comparing the GENCODE v14genes with the genome-wide set of posterior probabilities estimated byCENTIPEDE for the respective cell-types. The extent of a transcriptionfactor regulating each gene was determined by taking the sum of theweighed posterior probabilities for a given transcription factor mappingto the same chromosome. For each mapped motif the posterior probabilitywas weighted based on the distance to the transcription start site foreach gene. Comparison of transcription factor regulatory networks wascomputed as the correlation of each transcription factor in a given celltype with all transcription factors in the other cell type. Theresulting correlation matrix was hierarchically clustered using thePearson correlation coefficient and complete linkage.

Candidate IL2 enhancer analysis: ENCODE data on the UCSC genome browserwas inspected to identify putative IL2 enhancers in one or more celltypes that may be responsive to FDA approved immomodulatory drugs. Wescanned the intergenic region upstream of IL2 in hg19 for (i)enhancer-associated histone marks (H3K4me1 and H3K27ac), (ii) binding byone or more TFs as confirmed by ChIP-seq, and (iii) the TF pathway canbe targeted by a human therapeutic. This analysis identified IRF4 andSTAT3 binding sites in addition to the known NFAT-responsive elements.

Results

ATAC-seq Probes Chromatin Accessibility with Transposons

Hyperactive Tn5 transposase (Goryshin, J Biol Chem. 1998 273: 7367-7374;Adey, A. et al. Genome Biol 2010 11: R119, loaded in vitro with adaptersfor high-throughput DNA sequencing, can simultaneously fragment and taga genome with sequencing adapters (previously described as“tagmentation”). It was hypothesized that transposition by purified Tn5,a prokaryotic transposase, on small numbers of unfixed eukaryotic nucleiwould interrogate regions of accessible chromatin. An Assay forTransposase Accessible Chromatin followed by high-throughput sequencing(ATAC-seq) is described. ATAC-seq uses Tn5 transposase to integrate itsadapter payload into regions of accessible chromatin, whereas sterichindrance less accessible chromatin makes transposition less probable.Therefore, amplifiable DNA fragments suitable for high-throughputsequencing are preferentially generated at locations of open chromatin(FIG. 1a ). The entire assay and library construction can be carried outin a simple two-step process involving Tn5 insertion and PCR. Incontrast, published DNase- and FAIRE-seq protocols for assayingchromatin accessibility involve multi-step protocols and manypotentially loss-prone steps, such as adapter ligation, gelpurification, and crosslink reversal. For instance, a publishedDNase-seq protocol calls for approximately 44 steps, and two overnightincubations, while published FAIRE-seq protocols require two overnightincubations carried out over at least 3 days. Furthermore, theseprotocols require 1-50 million cells (FAIRE) or 50 million cells(DNase-seq), perhaps because of these complex workflows (FIG. 1b ). Incomparison to established methods, ATAC-seq enables rapid and efficientlibrary generation because assay and library preparation are carried outin a single enzymatic step.

Extensive analyses show that ATAC-seq provides accurate and sensitivemeasure of chromatin accessibility genome-wide. ATAC-seq was carried outon 50,000 and 500 unfixed nuclei isolated from GM12878 lymphoblastoidcell line (ENCODE Tier 1) for comparison and validation with chromatinaccessibility data sets, including DNase-seq and FAIRE-seq. At a locuspreviously highlighted by others, (FIG. 1c ), ATAC-seq has asignal-to-noise ratio similar to DNase-seq, which was generated fromapproximately 3 to 5 orders-of-magnitude more cells. Peak intensitieswere highly reproducible between technical replicates (R=0.98), andhighly correlated between ATAC-seq and DNase-seq (R=0.79 and R=0.83,FIG. 6), and it is noted that the majority of reads within peaks comefrom intersections of DNase and ATAC-seq peaks (FIG. 7). Comparing ourdata to DHSs identified in ENCODE DNase-seq data, receiver operatingcharacteristic (ROC) curves demonstrate a similar sensitivity andspecificity as DNase-seq (FIG. 8). It is also noted that ATAC-seq peakintensities correlate well with markers of active chromatin and not withtransposase sequence preference (FIGS. 9 and 10). Highly sensitive openchromatin detection is maintained even when using 5,000 or 500 humannuclei as starting material (FIGS. 8 and 11), although, under theconditions used, sensitivity is diminished for smaller numbers of inputmaterial, as can be seen in FIG. 1 c.

ATAC-seq Insert Sizes Disclose Nucleosome Positions

It was found that ATAC-seq paired-end reads produce detailed informationabout nucleosome packing and positioning. The insert size distributionof sequenced fragments from human chromatin has clear periodicity ofapproximately 200 base pairs, suggesting many fragments are protected byinteger multiples of nucleosomes (FIG. 2a ). This fragment sizedistribution also shows clear periodicity equal to the helical pitch ofDNA. By partitioning insert size distribution according to functionalclasses of chromatin as defined by previous models (Hoffman et al.Nucleic Acids Res. 2013 41: 827-841), and normalizing to the globalinsert distribution we observe clear class-specific enrichments acrossthis insert size distribution (FIG. 2b ), demonstrating that thesefunctional states of chromatin have an accessibility “fingerprint” thatcan be read out with ATAC-seq. These differential fragmentation patternsare consistent with the putative functional state of these classes, asCTCF-bound regions are enriched for short fragments of DNA, whiletranscription start sites are differentially depleted for mono-, di- andtri-nucleosome associated fragments. Transcribed and promoter flankingregions are enriched for longer multi-nucleosomal fragments, suggestingthey may represent more compacted forms of chromatin. Finally, priorstudies have shown that certain DNA sequences are refractory to nucleasedigestion and released as large, multi-nucleosome-sized fragments;subsequent studies showed that such fragments are condensedheterochromatin. Indeed repressed regions were found to be depleted forshort fragments and enriched for phased multi-nucleosomal inserts,consistent with their expected inaccessible state. These data suggestthat ATAC-seq reveals differentially accessible forms of chromatin,which have been long hypothesized to exist in vivo.

To explore nucleosome positioning within accessible chromatin in theGM12878 cell line, data was partitioned into reads generated fromputative nucleosome free regions of DNA, and reads likely derived fromnucleosome associated DNA (see FIG. 12). Using a simple heuristic thatpositively weights nucleosome associated fragments and negativelyweights nucleosome free fragments (see Methods), we calculated a datatrack used to call nucleosome positions within regions of accessiblechromatin (Chen, K. et al. Genome Research 2013 23, 341-351). An examplelocus (FIG. 3a ) contains a putative bidirectional promoter with CAGEdata showing two transcription start sites (TSS) separated by ˜700 bps.ATAC-seq reveals in fact two distinct nucleosome free regions, separatedby a single well-positioned mononucleosome (FIG. 3a ). Compared toMNase-seq, ATAC-seq data is more amenable to detecting nucleosomeswithin putative regulatory regions, as the majority of reads areconcentrated within accessible regions of chromatin (FIG. 3b ). Byaveraging signal across all active TSSs, it is noted thatnucleosome-free fragments are enriched at a canonical nucleosome-freepromoter region overlapping the TSS, while the nucleosome signal isenriched both upstream and downstream of the active TSS, and displayscharacteristic phasing of upstream and downstream nucleosomes (FIG. 3c). Because ATAC-seq reads are concentrated at regions of open chromatin,a strong nucleosome signal is seen at the +1 nucleosome, which decreasesat the +2, +3 and +4 nucleosomes, in contrast, MNase-seq nucleosomesignal increases at larger distances from the TSS likely due to overdigestion of more accessible nucleosomes. Additionally, MNase-seq (4billion reads) assays all nucleosomes, whereas reads generated fromATAC-seq (198 million paired reads) are concentrated at regulatorynucleosomes (FIG. 3b,c ). Using the nucleosome calls, putative distalregulatory regions and TSSs were further partitioned into regions thatwere nucleosome free and regions that were predicted to be nucleosomebound. It is noted that TSSs were enriched for nucleosome free regionswhen compared to distal elements, which tend to remain nucleosome rich(FIG. 3d ). These data suggest ATAC-seq can provide high-resolutionreadout of nucleosome associated and nucleosome free regions inregulatory elements genome wide.

ATAC-seq Reveals Patterns of Nucleosome-TF Spacing

ATAC-seq high-resolution regulatory nucleosome maps can be used tounderstand the relationship between nucleosomes and DNA binding factors.Using ChIP-seq data, we plotted the position of a variety of DNA bindingfactors with respect to the dyad of the nearest nucleosome. Unsupervisedhierarchical clustering (FIG. 3e ) revealed major classes of bindingwith respect to the proximal nucleosome, including 1) a stronglynucleosome avoiding group of factors with binding events stereotyped at˜180 bases from the nearest nucleosome dyad (comprising C-FOS, NFYA andIRF3), 2) a class of factors that “nestle up” precisely to the expectedend of nucleosome DNA contacts, which notably includes chromatin loopingfactors CTCF and cohesion complex subunits RAD21 and SMC3; 3) a largeclass of primarily TFs that have gradations of nucleosome avoiding ornucleosome-overlapping binding behavior, and 4) a class whose bindingsites tend to overlap nucleosome-associated DNA. Interestingly, thisfinal class includes chromatin remodeling factors such as CHD1 and SIN3Aas well as RNA polymerase II, which appears to be enriched at thenucleosome boundary. The interplay between precise nucleosomepositioning and locations of DNA binding factor immediately suggestsspecific hypotheses for mechanistic studies, a potential advantage ofATAC-seq.

ATAC-seq Footprints Infer Factor Occupancy Genome-Wide

ATAC-seq enables accurate inference of DNA binding factor occupancygenome-wide. DNA sequences directly occupied by DNA-binding proteinsshould be protected from transposition; the resulting sequence“footprint” reveals the presence of the DNA-binding protein at eachsite, analogous to DNase digestion footprints. At a specific CTCFbinding site on chromosome 1, we observed a clear footprint (a deepnotch of ATAC-seq signal), similar to footprints seen by DNase-seq, atthe precise location of the CTCF motif that coincides with the summit ofthe CTCF ChIP-seq signal in GM12878 cells (FIG. 4a ). The ATAC-seqsignal was averaged over all expected locations of CTCF within thegenome and observed a well-stereotyped “footprint” (FIG. 4b ). Similarresults were obtained for a variety of common TFs (for examples see FIG.13). We inferred the CTCF binding probability from motif consensusscore, evolutionary conservation, and ATAC-seq insertion data togenerate a posterior probability of CTCF binding at all loci (FIG. 4c )(Pique-Regi et al. Genome Research 2011 21 447-455). Results usingATAC-seq closely recapitulate ChIP-seq binding data in this cell lineand compare favorably to DNase-based factor occupancy inference (seeFIG. 14), suggesting that factor occupancy data can be extracted fromthese ATAC-seq data allowing reconstruction of regulatory networks.

ATAC-seq Enables Epigenomic Analysis on Clinical Timescales

ATAC-seq is rapid, information rich, and compatible with small numbersof cells and may serve as a powerful tool for personalized epigenomicsin the clinic. Specifically, one can envision “personal epigenomics” asgenome-scale information about chromatin generated from an individualfrom a standard clinical sample in a clinical timescale. ATAC-seq wasapplised to assay the personal T-cell epigenome of a healthy volunteervia standard serial blood draws, to demonstrate a workflow capable ofgenerating ATAC-seq libraries in clinical timescales. Using rapid T-cellenrichment and sample handling protocols, the total required time fromblood draw to sequencing was approximately 275 minutes (FIG. 5a ). Whencoupled with ongoing improvements to sequencing and analysis turn-aroundtimes, ATAC-seq can offer the possibility of a daily turn-around timefor a personal epigenomic map. To explore this possibility, ATAC-seq wasperformed on three consecutive days via standard blood draws from asingle individual (FIG. 5b ). As an exercise to consider how personalepigenomic maps may contain personalized regulatory information, weinvestigated ATAC-seq profile at the IL2 locus. IL-2 is a key cytokinethat drives T-cell growth and functions in inflammatory and autoimmunediseases. Furthermore, distinct drugs inhibit the activities ofdifferent transcription factors that bind putative IL2 enhancers in acontext-dependent manner. In principle, one might wish to identify thecausal transcription factor pathway in order to rationally targetinhibition without exposing the patient to drugs unlikely to serve thetherapeutic goal of IL-2 blockade. ATAC-seq shows that in the proband'sT-cells, only NFAT, but not two other drug targets, is engaging IL2(FIG. 5c ), providing clinically relevant information on the regulatorystate of this individual.

Using ATAC-seq footprints the occupancy profiles of 89 transcriptionfactors in proband T-cells were generated, enabling systematicreconstruction of regulatory networks. With this personalized regulatorymap, we compared the genomic distribution of the same 89 transcriptionfactors between GM12878 and proband CD4+ T-cells. Transcription factorsthat exhibit large variation in distribution between T-cells and B-cellsare enriched for T-cell specific factors (FIG. 5d ). This analysis showsNFAT is differentially regulating, while canonical CTCF occupancy ishighly correlated within these two cell types (FIG. 5d ). Supportingthis interpretation, it is noted that specific loci where NFAT islocalized nearby to known T-cell specific genes such as CD28 and a novellincRNA RP11-229C3.2 (FIG. 15). Additionally, ATAC-seq of CD4⁺ and CD8⁺T-cells, and monocytes isolated by fluorescence-activated cell sorting(FACS) from a single blood draw created an interpretative framework forthe personal epigenomes, and demonstrated that ATAC-seq is compatiblewith cellular enrichment using surface markers (FIG. 16). Separately,allele-specific chromatin accessibility has been shown to beparticularly relevant to our understanding of human disease. As a proofof principle we also used ATAC-seq to identify candidate allele-specificopen chromatin regions within the GM12878 cell line (FIG. 17). Theseresults demonstrate the feasibility of generating detailed personalizedgene regulatory networks from clinical samples, opening the door forfuture diagnostic applications.

Epigenomic studies of chromatin accessibility have yielded tremendousbiological insights, but are currently limited in application by theircomplex workflows and large cell number requirements. While,improvements of existing methods may enable them to reach the similarperformance, ATAC-seq in certain cases can offer substantial advantagesover existing technologies due to its speed, simplicity, and low inputcell number requirement. ATAC-seq is an information rich assay, allowingsimultaneous interrogation of factor occupancy, nucleosome positions inregulatory sites, and chromatin accessibility genome-wide. Theseinsights are derived from both the position of insertion and thedistribution of insert lengths captured during the transpositionreaction. While extant methods such as DNase- and MNase-seq can providesome subsets of the information in ATAC-seq, they each require separateassays with large cell numbers, which increases the time, cost, andlimits applicability to many systems. ATAC-seq also provides insert size“fingerprints” of biologically relevant genomic regions, suggesting thatit capture information on chromatin compaction. ATAC-seq may have broadapplicability, significantly add to the genomics toolkit, and improveour understanding of gene regulation, particularly when integrated withother powerful rare cell techniques, such as FACS, laser capturemicrodissection (LCM) and recent advancements in RNA-seq.

ATAC-seq may be used to generate “personal epigenomic” profiles on atimescale compatible with clinical decision-making. Optimized procedurescan transform a clinical blood sample to completed sequencing library in275 minutes. The reduced input requirements and rapid workflows, whencoupled with the recent introduction of rapid-turnaround high-throughputsequencing instruments, such as the MiSeq and HiSeq2500, should enableinvestigation of personalized epigenetic landscapes of selected tissuesboth in the lab and the clinic. ATAC-seq is compatible with FACS,enabling studies on carefully sorted and rare subpopulations fromprimary tissues. Cellular subpopulations selected at different points indevelopment and aging, and human diseases, including cancer,autoimmunity, and neuropsychiatric disorders are viable applications.

Example 2 Single-Cell ATAC-seq

Single-cell chromatin accessibility datasets were obtained using theATAC-seq protocol. To ensure that the ratio of transposase molecules toopen chromatin sites was kept nearly constant, the single-cell ATAC-seqassay was carried out by manipulating individual cells after an initialtransposition reaction.

Transposases can Serve as an Open-Chromatin Stain

It was observed that after in vitro insertion of sequencing adapter, theTn5 transposase remained tightly bound to the DNA and formed ahigh-affinity macromolecular complex that prevented dissociation of thegenerated ATAC-seq DNA fragments. To support this observation, Tn5transposase was loaded with fluorescently labeled DNA adapters, andallowed for visualization of regions of open chromatin within thenucleus of individual cells (FIG. 18). Additional electrophoreticmobility shift assays also indicated that the transposase remainedassociated to DNA after transposition.

Single-Cell ATAC-seq provides Unique Reads Characteristic of ChromosomalDNA

Since this fluorescence signal localized to the nucleus and wasdetectable even after transposition, the single-cell ATAC-seq experimentwas performed by keeping the transposed fragments in the nucleus duringsubsequent sorting and cell selection steps. A group of cells werepermeabilized, and the chromosomal DNA was transposed with Tn5transposase. The cells were kept under conditions that prevented theresulting ATAC-seq fragments from leaving the cell nucleus, (i.e.divalent cation was not chelated), and the individual cells were sortedinto independent PCR reactions for library preparation, as describedabove. This workflow significantly simplified the workflow forsingle-cell analysis and provided two additional advantages. First, thisabrogated any effect of the sorting process on the chromatin statebecause transposition preceded sorting. Second, it provided more robustATAC-seq signal, as cells were sorted directly into a PCR master mix andamplified. Using this workflow, 2,000-5,000 unique ATAC-seq reads percell were generated. These reads were enriched for known open chromatinsites in GM12878 cells (FIG. 19) and displayed characteristic periodicenrichments indicative of nucleosomes (FIG. 20).

Example 3 Quality Control

Assay for Transposase Accessible Chromatin (ATAC-seq) has been shown tobe compatible with many methods for cell collection and has also workedeffectively across many cell types and species. However, the followingprotocol has been optimized for human lymphoblastoid cells. Minorvariations (i.e. cell number, centrifugation speeds, and lysisconditions) may optimized for particular applications.

I. Cell Preparation

-   -   1. Harvest cells (no fixation), protocol to be defined by the        user.    -   2. Spin down 50,000 cells at 500×g for 5 min, 4° C.    -   3. Wash once with 50 μL of cold 1× PBS buffer. Spin down at        500×g for 5 min, 4° C.    -   4. Gently pipette to resuspend the cell pellet in 50 μL of cold        lysis buffer (10 mM Tris-HCl, pH 7.4, 10 mM NaCl, 3 mM MgCl₂,        0.1% IGEPAL CA-630). Spin down immediately at 500×g for 10 min,        4° C.    -   5. Discard the supernatant, and immediately continue to        transposition reaction.

II. Transposition Reaction and Purification

-   -   1. Make sure the cell pellet is set on ice.    -   2. To make the transposition reaction mix, combine the        following:        -   25 μL 2× TD Buffer (Illumina Cat #FC-121-1030)        -   2.5 μL Tn5 Transposes (Illumina Cat #FC-121-1030)        -   22.5 μL Nuclease Free H₂O        -   50 μl Total    -   3. Gently pipette to resuspend nuclei in the transposition        reaction mix.    -   4. Incubate the transposition reaction at 37° C. for 30 min.    -   5. Immediately following transposition, purify using a Qiagen        MinElute Kit.    -   6. Elute transposed DNA in 10 μL Elution Buffer (10mM Tris        buffer, pH 8).    -   7. Purified DNA can be stored at −20° C.

III. PCR Amplification

-   -   1. To amplify transposed DNA fragments, combine the following in        a PCR tube:        -   10 μL Transposed DNA        -   9.7 μL Nuclease Free H₂O        -   2.5 μL 25 μM Customized Nextera PCR Primer 1*        -   2.5 μL 25 μM Customized Nextera PCR Primer 2* [Barcode]        -   0.3 μL 100× SYBR Green I** (Invitrogen Cat #S-7563)        -   25 μL NEBNext High-Fidelity 2× PCR Master Mix (New England            Labs Cat #M0541)        -   50 μL Total * Complete list of primers are shown            above.**10,000× SYBR Green I is diluted in 10mM Tris buffer,            pH 8 to make a 100× working solution.    -   2. Cycle as follows:        -   (1) 72° C., 5 min        -   (2) 98° C., 30 sec        -   (3) 98° C., 10 sec        -   (4) 63° C., 30 sec        -   (5) 72° C., 1 min        -   (6) Repeat steps 3-5, 4x        -   (7) Hold at 4° C.    -   3. In order to reduce GC and size bias in PCR, the PCR reaction        is monitored using qPCR to stop amplification prior to        saturation. To run a qPCR side reaction, combine the following:        -   5 μL 5 cycles PCR amplified DNA        -   4.44 μL Nuclease Free H₂O        -   0.25 μL 25 μM Customized Nextera PCR Primer 1*        -   0.25 μL 25 μM Customized Nextera PCR Primer 2*        -   0.06 μL 100× SYBR Green I        -   5 μL NEBNext High-Fidelity 2× PCR Master Mix        -   15 μL Total * Complete list of primers available in Section            VI of this protocol    -   4. qPCR cycle as follows:        -   (1) 98° C., 30 sec        -   (2) 98° C., 10 sec        -   (3) 63° C., 30 sec        -   (4) 72° C., 1 min        -   (5) Repeat steps 2-4, 19×        -   (6) Hold at 4° C.    -   5. The additional number of cycles needed for the remaining 45        μL PCR reaction is determined as following:        -   (1) Plot linear Rn vs. Cycle        -   (2) Set 5000 RF threshold        -   (3) Calculate the # of cycle that is corresponded to ¼ of            maximum fluorescent intensity            -   If the # of cycle to be added lies in between two                cycles, the # is determined by taking the smaller                integer as the # of cycle to be added (i.e., blue and                pink samples)            -   If two samples have similar Ct values but differs in the                fluorescent intensities, calculate the # of cycle using                the sample with lower fluorescent intensity (i.e., red                and blue samples)    -   6. Run the remaining 45 μL PCR reaction to the correct # of        cycle. Cycle as follows:        -   (1) 98° C., 30 sec (2) 98° C., 10 sec (3) 63° C., 30 sec (4)            72° C., 1 min (5) Repeat steps 2-4, x times (6) Hold at 4°            C.    -   7. Purify amplified library using Qiagen PCR Cleanup Kit. Elute        the purified library in 20 μL Elution Buffer (10mM Tris Buffer,        pH 8). Be sure to dry the column before adding elution buffer.

IV. Library QC using Gel Electrophoresis

-   -   1. Dilute 1:20 100 bp NEB DNA ladder with 10mM Tris Buffer, pH        8.    -   2. Add 0.6 μL 10× SYBR Green I to every 5 μL of diluted ladder.    -   3. Mix 1:1 of the diluted ladder with 2× DNA loading dye.    -   4. Mix 1:1 of amplified library with 2× DNA loading dye.    -   5. Run amplified library on 5% Bio-Rad Mini-Protean TBE Precast        Gel (stored at 4° C.). Load 5 μL diluted ladder/DNA loading dye        mixture. Load 10 μL amplified library/DNA loading dye mixture.    -   6. Run at ˜100 mV for 45 min.    -   7. SYBR Green I dye has an excitation maximum at ˜488 nm and has        an emission maximum at ˜520 nm. DNA stained with SYBR Green I        dye can be visualized using a blue-light source or imaging        systems equipped with laser that emits at 488 nm. We typically        use Typhoon TRIO Variable Mode Imager from Amersham Biosciences        for visualization. Images are best obtained by digitizing at 100        microns pixel size resolution with a 520 nm band-pass emission        filter to screen out reflected and scattered excitation light        and background fluorescence.

V. Library Quantitation

We use qPCR based methods to quantify our ATAC-seq libraries. We havefound that other methods, such as Bioanalyzer and Qubit, can givemisleading and inaccurate results due to the large distribution ofinsert sizes. We recommend quantifying libraries using the KAPA LibraryQuant Kit for Illumina Sequencing Platforms (KAPABiosystems).

Although the foregoing embodiments have been described in some detail byway of illustration and example for purposes of clarity ofunderstanding, it is readily apparent to those of ordinary skill in theart in light of the above teachings that certain changes andmodifications can be made thereto without departing from the spirit orscope of the appended claims.

1-77. (canceled)
 78. A method for analyzing a biological sample,comprising: (a) contacting chromatin of a genome region of saidbiological sample with an insertional enzyme complex to produce taggednucleic acid molecules, wherein said insertional enzyme complex does notcomprise an antibody specific to a protein that is part of saidchromatin; and (b) performing a nucleic acid assay on said taggednucleic acid molecules or derivatives thereof, to provide sequenceinformation of said tagged nucleic acid molecules or derivativesthereof.
 79. The method of claim 78, further comprising generating arepresentation of epigenetic features of said genome region at least inpart by mapping said sequence information to said genome region.
 80. Themethod of claim 78, wherein said biological sample is a cell or anucleus.
 81. The method of claim 80, further comprising lysing said cellor said nucleus.
 82. The method of claim 80, further comprisingpermeabilizing said cell or said nucleus to permit said insertionalenzyme complex to access said chromatin.
 83. The method of claim 82,wherein said permeabilizing is configured to minimally perturb saidchromatin of said cell or said nucleus.
 84. The method of claim 82,wherein said cell or said nucleus is permeabilized with a reagentconfigured to permit said insertional enzyme complex to access saidchromatin.
 85. The method of claim 84, wherein said reagent comprisesNP40, digitonin, tween, streptolysin, or a cationic lipid.
 86. Themethod of claim 82, wherein said cell or said nucleus is permeabilizedby hypotonic shock or ultrasonication.
 87. The method of claim 78,wherein said insertional enzyme comprises a transposase.
 88. The methodof claim 87, wherein said transposase is a Tn5 transposase or derivedfrom a Tn5 transposase.
 89. The method of claim 88, wherein saidtransposase is a hyperactive Tn5 transposase.
 90. The method of claim78, wherein said insertional enzyme complex comprises a first nucleicacid insert element comprising a first adapter sequence.
 91. The methodof claim 90, wherein said first adapter sequence comprises a firstsequencing adapter sequence.
 92. The method of claim 90, wherein saidfirst adapter sequence comprises a barcode sequence.
 93. The method ofclaim 90, wherein said first adapter sequence comprises a first primersequence.
 94. The method of claim 90, wherein said insertional enzymecomplex further comprises a second nucleic acid insert elementcomprising a second adapter sequence.
 95. The method of claim 94,wherein said second adapter sequence comprises a second sequencingadapter sequence.
 96. The method of claim 94, wherein said secondadapter sequence comprises a barcode sequence.
 97. The method of claim94, wherein said second adapter sequence comprises a second primersequence.
 98. The method of claim 78, further comprising subjecting saidtagged nucleic acid molecules to one or more reactions.
 99. The methodof claim 98, wherein said one or more reactions comprise a nucleic acidamplification reaction.
 100. The method of claim 99, wherein saidnucleic acid amplification reaction is configured to add one or morefunctional sequences to said tagged nucleic acid molecules orderivatives thereof, wherein said one or more functional sequences arecompatible with a selected next generation sequencing platform.